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神经追踪基频:嗓音特征的影响。

Neural tracking of the fundamental frequency of the voice: The effect of voice characteristics.

机构信息

ExpORL, Department of Neurosciences, KU Leuven, Leuven, Belgium.

出版信息

Eur J Neurosci. 2021 Jun;53(11):3640-3653. doi: 10.1111/ejn.15229. Epub 2021 Apr 27.

DOI:10.1111/ejn.15229
PMID:33861480
Abstract

Traditional electrophysiological methods to study temporal auditory processing of the fundamental frequency of the voice (f0) often use unnaturally repetitive stimuli. In this study, we investigated f0 processing of meaningful continuous speech. EEG responses evoked by stories in quiet were analysed with a novel method based on linear modelling that characterizes the neural tracking of the f0. We studied both the strength and the spatio-temporal properties of the f0-tracking response. Moreover, different samples of continuous speech (six stories by four speakers: two male and two female) were used to investigate the effect of voice characteristics on the f0 response. The results indicated that response strength is inversely related to f0 frequency and rate of f0 change throughout the story. As a result, the male-narrated stories in this study (low and steady f0) evoked stronger f0-tracking compared to female-narrated stories (high and variable f0), for which many responses were not significant. The spatio-temporal analysis revealed that f0-tracking response generators were not fixed in the brainstem but were voice-dependent as well. Voices with high and variable f0 evoked subcortically dominated responses with a latency between 7 and 12 ms. Voices with low and steady f0 evoked responses that are both subcortically (latency of 13-15 ms) and cortically (latency of 23-26 ms) generated, with the right primary auditory cortex as a likely cortical source. Finally, additional experiments revealed that response strength greatly improves for voices with strong higher harmonics, which is particularly useful to boost the small responses evoked by voices with high f0.

摘要

传统的电生理方法常使用不自然重复的刺激来研究语音基频(f0)的时间听觉处理。在这项研究中,我们研究了有意义的连续语音的 f0 处理。使用基于线性建模的新方法分析了在安静环境下故事引发的 EEG 反应,该方法可以描述 f0 的神经跟踪特性。我们研究了 f0 跟踪反应的强度和时空特性。此外,我们使用不同的连续语音样本(四个说话者的六个故事:两个男性和两个女性)来研究语音特征对 f0 反应的影响。结果表明,反应强度与 f0 频率和故事中 f0 变化率成反比。因此,与女性讲述的故事(高且多变的 f0)相比,本研究中男性讲述的故事(低且稳定的 f0)引起的 f0 跟踪反应更强,其中许多反应不显著。时空分析表明,f0 跟踪反应发生器不是固定在脑干中的,而是依赖于语音的。具有高且多变 f0 的声音会引起下皮质主导的反应,潜伏期在 7 到 12 毫秒之间。具有低且稳定 f0 的声音会引起下皮质(潜伏期为 13-15 毫秒)和皮质(潜伏期为 23-26 毫秒)产生的反应,右初级听觉皮层可能是皮质源。最后,额外的实验表明,对于具有强高次谐波的声音,反应强度会大大提高,这对于增强具有高 f0 的声音引起的小反应特别有用。

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