Speech intelligibility changes the temporal evolution of neural speech tracking.
Speech intelligibility changes the temporal evolution of neural speech tracking.
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语音清晰度改变了神经语音跟踪的时间演化。
DOI：
10.1016/j.neuroimage.2023.119894
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发表时间：
2023
期刊：
影响因子：
5.7
通讯作者：
Chen YP
中科院分区：
文献类型：
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作者：
Chen YP
收听信号质量较差的语音具有挑战性。对退化语音的神经语音跟踪已被用来促进对大脑过程和语音清晰度如何相互关联的理解。然而，神经语音跟踪的时间动态及其与语音清晰度的关系尚不清楚。在目前的 MEG 研究中，我们利用了时间响应函数 (TRF)，该函数已用于描述从可理解到不可理解的降级语音的梯度上的语音跟踪的时间过程。此外，我们使用神经语音跟踪的相互关联的方面（例如，语音包络重建、语音脑相干性和宽带相干谱的组成部分）来支持我们在 TRF 中的发现。我们的 TRF 分析得出了声码的显着时间差异效应：∼50–110 ms (M50TRF)、∼175–230 ms (M200TRF) 和∼315–380 ms (M350TRF)。可懂度的降低伴随着早期峰值响应 M50TRF 的大幅增加，但 M200TRF 中的响应大幅降低。在 M350TRF 的后期响应中，最大响应出现在仍可理解的退化语音中，然后随着清晰度的降低而下降。此外，我们将 TRF 组件与其他神经“跟踪”测量相关联，发现 M50TRF 和 M200TRF 在宽带相干谱的中心频率移动中发挥着不同的作用。总的来说，我们的研究强调了神经语音跟踪的时间分辨计算和相干谱分解的重要性，并提供了对退化语音处理的更好理解。
Listening to speech with poor signal quality is challenging. Neural speech tracking of degraded speech has been used to advance the understanding of how brain processes and speech intelligibility are interrelated. However, the temporal dynamics of neural speech tracking and their relation to speech intelligibility are not clear. In the present MEG study, we exploited temporal response functions (TRFs), which has been used to describe the time course of speech tracking on a gradient from intelligible to unintelligible degraded speech. In addition, we used inter-related facets of neural speech tracking (e.g., speech envelope reconstruction, speech-brain coherence, and components of broadband coherence spectra) to endorse our findings in TRFs. Our TRF analysis yielded marked temporally differential effects of vocoding: ∼50–110 ms (M50TRF), ∼175–230 ms (M200TRF), and ∼315–380 ms (M350TRF). Reduction of intelligibility went along with large increases of early peak responses M50TRF, but strongly reduced responses in M200TRF. In the late responses M350TRF, the maximum response occurred for degraded speech that was still comprehensible then declined with reduced intelligibility. Furthermore, we related the TRF components to our other neural “tracking“ measures and found that M50TRFand M200TRFplay a differential role in the shifting center frequency of the broadband coherence spectra. Overall, our study highlights the importance of time-resolved computation of neural speech tracking and decomposition of coherence spectra and provides a better understanding of degraded speech processing.