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潜伏的神经动力学编码了语音中的时间上下文。

Latent neural dynamics encode temporal context in speech.

机构信息

Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States; Department of Mathematics and Statistics, Boston University, Boston, MA 02215, United States.

Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, United States; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.

出版信息

Hear Res. 2023 Sep 15;437:108838. doi: 10.1016/j.heares.2023.108838. Epub 2023 Jul 4.

Abstract

Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.

摘要

直接从人类听觉皮层进行的神经记录已经证明了对辅音和元音的声学-语音特征的编码。神经反应还编码了与时间相关的不同的声学幅度线索,例如在句子开头出现的无声期后或每个音节的元音开始时出现的那些线索。在这里,我们使用了一个群组降秩回归模型来表明,皮质的分布式反应支持语音中时间上下文的低维潜在状态表示。每个时间线索比所有其他语音特征都捕获更多的独特方差,并在潜在空间中表现出旋转或周期性动态,这些动态来自于广泛分布在颞上回的活动。我们提出,这些空间分布的时间信号可以为单个语音特征的并发处理提供时间上下文,并可能在时间上绑定,以组成更高阶的语音(例如,词级)表示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/74e1/11182421/9cd2b7482614/nihms-1997385-f0001.jpg

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