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被关注信息流的行为描述增强了神经追踪。

Behavioral Account of Attended Stream Enhances Neural Tracking.

作者信息

Huet Moïra-Phoebé, Micheyl Christophe, Parizet Etienne, Gaudrain Etienne

机构信息

Laboratoire Vibrations Acoustique, Institut National des Sciences Appliquées de Lyon, Université de Lyon, Villeurbanne, France.

CNRS UMR 5292, INSERM U1028, Auditory Cognition and Psychoacoustics Team, Lyon Neuroscience Research Center, Lyon, France.

出版信息

Front Neurosci. 2021 Dec 13;15:674112. doi: 10.3389/fnins.2021.674112. eCollection 2021.

DOI:10.3389/fnins.2021.674112
PMID:34966252
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8710602/
Abstract

During the past decade, several studies have identified electroencephalographic (EEG) correlates of selective auditory attention to speech. In these studies, typically, listeners are instructed to focus on one of two concurrent speech streams (the "target"), while ignoring the other (the "masker"). EEG signals are recorded while participants are performing this task, and subsequently analyzed to recover the attended stream. An assumption often made in these studies is that the participant's attention can remain focused on the target throughout the test. To check this assumption, and assess when a participant's attention in a concurrent speech listening task was directed toward the target, the masker, or neither, we designed a behavioral listen-then-recall task (the Long-SWoRD test). After listening to two simultaneous short stories, participants had to identify keywords from the target story, randomly interspersed among words from the masker story and words from neither story, on a computer screen. To modulate task difficulty, and hence, the likelihood of attentional switches, masker stories were originally uttered by the same talker as the target stories. The masker voice parameters were then manipulated to parametrically control the similarity of the two streams, from clearly dissimilar to almost identical. While participants listened to the stories, EEG signals were measured and subsequently, analyzed using a temporal response function (TRF) model to reconstruct the speech stimuli. Responses in the behavioral recall task were used to infer, retrospectively, when attention was directed toward the target, the masker, or neither. During the model-training phase, the results of these behavioral-data-driven inferences were used as inputs to the model in addition to the EEG signals, to determine if this additional information would improve stimulus reconstruction accuracy, relative to performance of models trained under the assumption that the listener's attention was unwaveringly focused on the target. Results from 21 participants show that information regarding the actual - as opposed to, assumed - attentional focus can be used advantageously during model training, to enhance subsequent (test phase) accuracy of auditory stimulus-reconstruction based on EEG signals. This is the case, especially, in challenging listening situations, where the participants' attention is less likely to remain focused entirely on the target talker. In situations where the two competing voices are clearly distinct and easily separated perceptually, the assumption that listeners are able to stay focused on the target is reasonable. The behavioral recall protocol introduced here provides experimenters with a means to behaviorally track fluctuations in auditory selective attention, including, in combined behavioral/neurophysiological studies.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/41e70442fdc4/fnins-15-674112-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/cb876a667ad0/fnins-15-674112-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/5ce58f6ff25a/fnins-15-674112-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/81ac3b5b6a70/fnins-15-674112-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/e860e089c88f/fnins-15-674112-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/41e70442fdc4/fnins-15-674112-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/cb876a667ad0/fnins-15-674112-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/5ce58f6ff25a/fnins-15-674112-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/81ac3b5b6a70/fnins-15-674112-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/e860e089c88f/fnins-15-674112-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d851/8710602/41e70442fdc4/fnins-15-674112-g005.jpg
摘要

在过去十年中,多项研究已确定了对语音选择性听觉注意的脑电图(EEG)相关指标。在这些研究中,通常会指示听众专注于两个同时出现的语音流之一(“目标”),而忽略另一个(“掩蔽声”)。在参与者执行此任务时记录EEG信号,随后进行分析以恢复被关注的语音流。这些研究中经常做出的一个假设是,参与者的注意力在整个测试过程中都可以保持集中在目标上。为了检验这一假设,并评估参与者在同时进行的语音聆听任务中何时将注意力指向目标、掩蔽声或两者都未指向,我们设计了一个行为听后回忆任务(长单词识别测试)。在听完两个同时播放的短篇小说后,参与者必须在电脑屏幕上从目标故事中识别关键词,这些关键词随机穿插在掩蔽声故事中的单词和两者都无关的单词之中。为了调节任务难度,进而调节注意力切换的可能性,掩蔽声故事最初由与目标故事相同的讲述者说出。然后对掩蔽声的语音参数进行操作,以参数方式控制两个语音流的相似度,从明显不同到几乎相同。当参与者听故事时,测量EEG信号,随后使用时间响应函数(TRF)模型进行分析以重建语音刺激。行为回忆任务中的反应用于回顾性推断注意力何时指向目标、掩蔽声或两者都未指向。在模型训练阶段,除了EEG信号之外,这些基于行为数据的推断结果还被用作模型的输入,以确定相对于在听众注意力始终坚定地集中在目标这一假设下训练的模型的性能,此额外信息是否会提高刺激重建的准确性。21名参与者的结果表明,关于实际(而非假设)注意力焦点的信息在模型训练期间可以被有效地利用,以提高基于EEG信号的听觉刺激重建在后续(测试阶段)的准确性。尤其在具有挑战性的聆听情境中更是如此,在这种情境下参与者的注意力不太可能完全集中在目标讲述者身上。在两个竞争声音明显不同且在感知上易于分离地情况下,听众能够保持专注于目标的假设是合理的。这里介绍的行为回忆方案为实验者提供了一种在行为上跟踪听觉选择性注意波动的方法,包括在行为/神经生理学联合研究中。

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本文引用的文献

1
Vocal and semantic cues for the segregation of long concurrent speech stimuli in diotic and dichotic listening-The Long-SWoRD test.用于在同听和对听中分离长时并发言语刺激的语音和语义线索——长词测试。
J Acoust Soc Am. 2022 Mar;151(3):1557. doi: 10.1121/10.0007225.
2
Are They Calling My Name? Attention Capture Is Reflected in the Neural Tracking of Attended and Ignored Speech.他们在叫我的名字吗?注意力捕获反映在对被关注和被忽略语音的神经追踪中。
Front Neurosci. 2021 Mar 22;15:643705. doi: 10.3389/fnins.2021.643705. eCollection 2021.
3
Effect of number and placement of EEG electrodes on measurement of neural tracking of speech.
脑电图电极数量和位置对言语神经追踪测量的影响。
PLoS One. 2021 Feb 11;16(2):e0246769. doi: 10.1371/journal.pone.0246769. eCollection 2021.
4
Decoding the Attended Speaker From EEG Using Adaptive Evaluation Intervals Captures Fluctuations in Attentional Listening.使用自适应评估间隔从脑电图中解码被关注的说话者可捕捉注意力倾听中的波动。
Front Neurosci. 2020 Jun 16;14:603. doi: 10.3389/fnins.2020.00603. eCollection 2020.
5
Poor early cortical differentiation of speech predicts perceptual difficulties of severely hearing-impaired listeners in multi-talker environments.早期皮质言语分化不良预测重度听力障碍者在多说话人环境中感知困难。
Sci Rep. 2020 Apr 9;10(1):6141. doi: 10.1038/s41598-020-63103-7.
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Where is the cocktail party? Decoding locations of attended and unattended moving sound sources using EEG.鸡尾酒会在哪里?使用 EEG 解码有注意和无注意移动声源的位置。
Neuroimage. 2020 Jan 15;205:116283. doi: 10.1016/j.neuroimage.2019.116283. Epub 2019 Oct 17.
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EEG decoding of the target speaker in a cocktail party scenario: considerations regarding dynamic switching of talker location.鸡尾酒会场景中目标说话人的 EEG 解码:关于说话人位置动态切换的考虑因素。
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Does good perception of vocal characteristics relate to better speech-on-speech intelligibility for cochlear implant users?良好的嗓音特征感知是否与人工耳蜗使用者的言语-言语可懂度更好相关?
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Neural tracking of the speech envelope in cochlear implant users.人工耳蜗使用者语音包络的神经追踪。
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A Comparison of Regularization Methods in Forward and Backward Models for Auditory Attention Decoding.听觉注意力解码的前向和后向模型中正则化方法的比较
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