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言语声包络与想象言语时脑电振荡的同步性。

Synchronization between overt speech envelope and EEG oscillations during imagined speech.

机构信息

Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan.

Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan.

出版信息

Neurosci Res. 2020 Apr;153:48-55. doi: 10.1016/j.neures.2019.04.004. Epub 2019 Apr 18.

Abstract

Neural oscillations synchronize with the periodicity of external stimuli such as the rhythm of the speech amplitude envelope. This synchronization induces a speech-specific, replicable neural phase pattern across trials and enables perceived speech to be classified. In this study, we hypothesized that neural oscillations during articulatory imagination of speech could also synchronize with the rhythm of speech imagery. To validate the hypothesis, after replacing the imagined speech with overt speech due to the physically unobservable nature of imagined speech, we investigated (1) whether the EEG-based regressed speech envelopes correlate with the overt speech envelope and (2) whether EEG during the imagined speech can classify speech stimuli with different envelopes. The variability of the duration of the imagined speech across trials was corrected using dynamic time warping. The classification was based on the distance between a test data and a template waveform of each class. Results showed a significant correlation between the EEG-based regressed envelope and the overt speech envelope. The average classification accuracy was 38.5%, which is significantly above the rate of chance (33.3%). These results demonstrate the synchronization between EEG during the imagined speech and the envelope of the overt counterpart.

摘要

神经振荡与外部刺激的周期性同步,例如语音幅度包络的节奏。这种同步会在试验中诱导出特定于语音的可复制神经相位模式,并能够对感知到的语音进行分类。在这项研究中,我们假设语音想象期间的神经振荡也可以与语音想象的节奏同步。为了验证假设,由于想象中的语音的物理不可观测性质,我们用实际的语音代替了想象中的语音后,我们研究了(1)基于 EEG 的回归语音包络是否与实际语音包络相关,以及(2)在想象语音期间的 EEG 是否可以对具有不同包络的语音刺激进行分类。通过动态时间规整校正了试验中想象的语音持续时间的变化性。分类是基于每个类的测试数据和模板波形之间的距离。结果表明,基于 EEG 的回归包络与实际语音包络之间存在显著相关性。平均分类准确率为 38.5%,明显高于随机水平(33.3%)。这些结果表明,想象中的语音期间的 EEG 与实际语音的包络之间存在同步。

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