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注意的连续语音在不同类型干扰下的神经编码。

Neural Encoding of Attended Continuous Speech under Different Types of Interference.

机构信息

University of Cambridge.

出版信息

J Cogn Neurosci. 2018 Nov;30(11):1606-1619. doi: 10.1162/jocn_a_01303. Epub 2018 Jul 13.

DOI:10.1162/jocn_a_01303
PMID:30004849
Abstract

We examined how attention modulates the neural encoding of continuous speech under different types of interference. In an EEG experiment, participants attended to a narrative in English while ignoring a competing stream in the other ear. Four different types of interference were presented to the unattended ear: a different English narrative, a narrative in a language unknown to the listener (Spanish), a well-matched nonlinguistic acoustic interference (Musical Rain), and no interference. Neural encoding of attended and unattended signals was assessed by calculating cross-correlations between their respective envelopes and the EEG recordings. Findings revealed more robust neural encoding for the attended envelopes compared with the ignored ones. Critically, however, the type of the interfering stream significantly modulated this process, with the fully intelligible distractor (English) causing the strongest encoding of both attended and unattended streams and latest dissociation between them and nonintelligible distractors causing weaker encoding and early dissociation between attended and unattended streams. The results were consistent over the time course of the spoken narrative. These findings suggest that attended and unattended information can be differentiated at different depths of processing analysis, with the locus of selective attention determined by the nature of the competing stream. They provide strong support to flexible accounts of auditory selective attention.

摘要

我们研究了在不同类型的干扰下,注意力如何调节连续语音的神经编码。在一项 EEG 实验中,参与者用英语听一则叙述,同时忽略另一只耳朵里的竞争流。未被注意的耳朵会受到四种不同类型的干扰:另一个英语叙述、听众不熟悉的语言(西班牙语)的叙述、匹配良好的非语言声音干扰(音乐雨)和无干扰。通过计算它们各自的包络与 EEG 记录之间的互相关,评估了被注意和未被注意信号的神经编码。结果表明,与未被注意的信号相比,被注意的信号的神经编码更加强烈。然而,至关重要的是,干扰流的类型显著调节了这个过程,完全可理解的干扰(英语)导致被注意和未被注意的流的最强编码,以及它们之间最晚的分离,而非可理解的干扰导致较弱的编码和被注意和未被注意的流之间的早期分离。这些结果在口语叙述的时间过程中是一致的。这些发现表明,在不同的处理分析深度上,可以区分被注意和未被注意的信息,选择性注意的焦点由竞争流的性质决定。它们为听觉选择性注意的灵活解释提供了有力支持。

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