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在口语处理过程中,Delta 和 theta 波段神经追踪对多级语音特征的锐化和预测编码具有不同的作用。

Distinct roles of delta- and theta-band neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing.

机构信息

Hearing Theme, National Institute for Health Research Nottingham Biomedical Research Centre, Nottingham, UK.

Academic Unit of Mental Health and Clinical Neurosciences, School of Medicine, The University of Nottingham, Nottingham, UK.

出版信息

Hum Brain Mapp. 2023 Dec 1;44(17):6149-6172. doi: 10.1002/hbm.26503. Epub 2023 Oct 11.

Abstract

The brain tracks and encodes multi-level speech features during spoken language processing. It is evident that this speech tracking is dominant at low frequencies (<8 Hz) including delta and theta bands. Recent research has demonstrated distinctions between delta- and theta-band tracking but has not elucidated how they differentially encode speech across linguistic levels. Here, we hypothesised that delta-band tracking encodes prediction errors (enhanced processing of unexpected features) while theta-band tracking encodes neural sharpening (enhanced processing of expected features) when people perceive speech with different linguistic contents. EEG responses were recorded when normal-hearing participants attended to continuous auditory stimuli that contained different phonological/morphological and semantic contents: (1) real-words, (2) pseudo-words and (3) time-reversed speech. We employed multivariate temporal response functions to measure EEG reconstruction accuracies in response to acoustic (spectrogram), phonetic and phonemic features with the partialling procedure that singles out unique contributions of individual features. We found higher delta-band accuracies for pseudo-words than real-words and time-reversed speech, especially during encoding of phonetic features. Notably, individual time-lag analyses showed that significantly higher accuracies for pseudo-words than real-words started at early processing stages for phonetic encoding (<100 ms post-feature) and later stages for acoustic and phonemic encoding (>200 and 400 ms post-feature, respectively). Theta-band accuracies, on the other hand, were higher when stimuli had richer linguistic content (real-words > pseudo-words > time-reversed speech). Such effects also started at early stages (<100 ms post-feature) during encoding of all individual features or when all features were combined. We argue these results indicate that delta-band tracking may play a role in predictive coding leading to greater tracking of pseudo-words due to the presence of unexpected/unpredicted semantic information, while theta-band tracking encodes sharpened signals caused by more expected phonological/morphological and semantic contents. Early presence of these effects reflects rapid computations of sharpening and prediction errors. Moreover, by measuring changes in EEG alpha power, we did not find evidence that the observed effects can be solitarily explained by attentional demands or listening efforts. Finally, we used directed information analyses to illustrate feedforward and feedback information transfers between prediction errors and sharpening across linguistic levels, showcasing how our results fit with the hierarchical Predictive Coding framework. Together, we suggest the distinct roles of delta and theta neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing.

摘要

大脑在处理口语时会跟踪和编码多层次的语音特征。显然,这种语音跟踪在低频(<8 Hz)时占主导地位,包括 delta 和 theta 频段。最近的研究已经证明了 delta 和 theta 频段跟踪之间的区别,但尚未阐明它们如何在不同的语言层次上对语音进行不同的编码。在这里,我们假设 delta 频段跟踪编码预测误差(增强对意外特征的处理),而 theta 频段跟踪编码神经锐化(增强对预期特征的处理),当人们感知具有不同语言内容的语音时。当正常听力的参与者注意到包含不同语音/形态和语义内容的连续听觉刺激时,记录了 EEG 反应:(1)真实词,(2)假词和(3)语音反转。我们采用多元时间响应函数来测量 EEG 对声学(频谱图)、语音和音位特征的重建准确性,使用偏分程序单独提取各个特征的独特贡献。我们发现,假词的 delta 频段准确性高于真实词和语音反转词,尤其是在语音特征的编码过程中。值得注意的是,个体时滞分析表明,与真实词相比,假词的准确性显著提高,开始于语音编码的早期阶段(特征后<100 毫秒),而在声学和音位编码的后期阶段(特征后分别为>200 和 400 毫秒)。另一方面,当刺激具有更丰富的语言内容时(真实词>假词>语音反转词),theta 频段的准确性更高。这些效应也开始于早期阶段(特征后<100 毫秒),在对所有单个特征或对所有特征进行组合的编码过程中。我们认为,这些结果表明,delta 频段跟踪可能在预测编码中发挥作用,导致对假词的跟踪增强,因为存在意外/未预测的语义信息,而 theta 频段跟踪编码由更预期的语音/形态和语义内容引起的信号锐化。这些效应的早期存在反映了锐化和预测误差的快速计算。此外,通过测量 EEG alpha 功率的变化,我们没有发现证据表明,所观察到的效应可以单独用注意力需求或听力努力来解释。最后,我们使用有向信息分析来说明预测误差和锐化在语言层次之间的前馈和反馈信息传递,展示了我们的结果如何符合分层预测编码框架。总之,我们认为 delta 和 theta 神经跟踪在口语处理过程中对多层次语音特征的锐化和预测编码具有不同的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdf2/10619373/940aeea99ad5/HBM-44-6149-g001.jpg

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