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大脑追踪关于听觉场景的多种预测。

The Brain Tracks Multiple Predictions About the Auditory Scene.

作者信息

Brace Kelin M, Sussman Elyse S

机构信息

Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, United States.

出版信息

Front Hum Neurosci. 2021 Nov 3;15:747769. doi: 10.3389/fnhum.2021.747769. eCollection 2021.

Abstract

The predictable rhythmic structure is important to most ecologically relevant sounds for humans, such as is found in the rhythm of speech or music. This study addressed the question of how rhythmic predictions are maintained in the auditory system when there are multiple perceptual interpretations occurring simultaneously and emanating from the same sound source. We recorded the electroencephalogram (EEG) while presenting participants with a tone sequence that had two different tone feature patterns, one based on the sequential rhythmic variation in tone duration and the other on sequential rhythmic variation in tone intensity. Participants were presented with the same sound sequences and were instructed to listen for the intensity pattern (ignore fluctuations in duration) and press a response key to detected pattern deviants (attend intensity pattern task); to listen to the duration pattern (ignore fluctuations in intensity) and make a button press to duration pattern deviants (attend duration pattern task), and to watch a movie and ignore the sounds presented to their ears (attend visual task). Both intensity and duration patterns occurred predictably 85% of the time, thus the key question involved evaluating how the brain treated the irrelevant feature patterns (standards and deviants) while performing an auditory or visual task. We expected that task-based feature patterns would have a more robust brain response to attended standards and deviants than the unattended feature patterns. Instead, we found that the neural entrainment to the rhythm of the standard attended patterns had similar power to the standard of the unattended feature patterns. In addition, the infrequent pattern deviants elicited the event-related brain potential called the mismatch negativity component (MMN). The MMN elicited by task-based feature pattern deviants had a similar amplitude to MMNs elicited by unattended pattern deviants that were unattended because they were not the target pattern or because the participant ignored the sounds and watched a movie. Thus, these results demonstrate that the brain tracks multiple predictions about the complexities in sound streams and can automatically track and detect deviations with respect to these predictions. This capability would be useful for switching attention rapidly among multiple objects in a busy auditory scene.

摘要

对于人类而言,可预测的节奏结构对于大多数与生态相关的声音都很重要,比如在言语或音乐节奏中所发现的那样。本研究探讨了这样一个问题:当同时存在多种感知解释且都源自同一声源时,听觉系统是如何维持节奏预测的。我们在向参与者呈现具有两种不同音调特征模式的音调序列时记录脑电图(EEG),一种基于音调持续时间的顺序节奏变化,另一种基于音调强度的顺序节奏变化。向参与者呈现相同的声音序列,并指示他们聆听强度模式(忽略持续时间的波动)并按下响应键以检测模式偏差(专注于强度模式任务);聆听持续时间模式(忽略强度的波动)并按下按钮以响应持续时间模式偏差(专注于持续时间模式任务),以及观看电影并忽略传入耳中的声音(专注于视觉任务)。强度和持续时间模式在85%的时间里都是可预测地出现,因此关键问题在于评估大脑在执行听觉或视觉任务时如何处理不相关的特征模式(标准模式和偏差模式)。我们预期基于任务的特征模式对于专注的标准模式和偏差模式会比未被关注的特征模式产生更强健的大脑反应。然而,我们发现对专注的标准模式节奏的神经夹带与未被关注的特征模式的标准具有相似的强度。此外,不常见的模式偏差会引发一种称为失配负波成分(MMN)的事件相关脑电位。基于任务的特征模式偏差所引发的MMN与未被关注的模式偏差所引发的MMN具有相似的幅度,未被关注的模式偏差是因为它们不是目标模式,或者因为参与者忽略了声音并观看了电影。因此,这些结果表明大脑能够追踪关于声音流复杂性的多种预测,并且能够自动追踪并检测相对于这些预测的偏差。这种能力对于在繁忙的听觉场景中快速在多个对象之间切换注意力会很有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/792b/8595267/19c337b5077f/fnhum-15-747769-g0001.jpg

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