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Human Sensorimotor Cortex Control of Directly Measured Vocal Tract Movements during Vowel Production.人类感觉运动皮层对元音产生期间直接测量的声道运动的控制。
J Neurosci. 2018 Mar 21;38(12):2955-2966. doi: 10.1523/JNEUROSCI.2382-17.2018. Epub 2018 Feb 8.
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Brain-Computer Interfaces for Augmentative and Alternative Communication: A Tutorial.脑机接口在辅助和替代沟通中的应用:教程。
Am J Speech Lang Pathol. 2018 Feb 6;27(1):1-12. doi: 10.1044/2017_AJSLP-16-0244.
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Decoding spoken phonemes from sensorimotor cortex with high-density ECoG grids.利用高密度 ECoG 网格从感觉运动皮层解码口语音素。
Neuroimage. 2018 Oct 15;180(Pt A):301-311. doi: 10.1016/j.neuroimage.2017.10.011. Epub 2017 Oct 7.
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Brain-to-text: decoding spoken phrases from phone representations in the brain.脑到文本:从大脑中的语音表征解码口语短语。
Front Neurosci. 2015 Jun 12;9:217. doi: 10.3389/fnins.2015.00217. eCollection 2015.
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Direct classification of all American English phonemes using signals from functional speech motor cortex.利用功能性言语运动皮层的信号对所有美式英语音素进行直接分类。
J Neural Eng. 2014 Jun;11(3):035015. doi: 10.1088/1741-2560/11/3/035015. Epub 2014 May 19.
7
What does motor efference copy represent? Evidence from speech production.运动传出副本代表什么?来自言语产生的证据。
J Neurosci. 2013 Oct 9;33(41):16110-6. doi: 10.1523/JNEUROSCI.2137-13.2013.
8
Vowel category boundaries enhance cortical and behavioral responses to speech feedback alterations.元音范畴边界增强了皮质和行为对语音反馈变化的反应。
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9
Speech production as state feedback control.言语产生作为状态反馈控制。
Front Hum Neurosci. 2011 Oct 25;5:82. doi: 10.3389/fnhum.2011.00082. eCollection 2011.
10
Error-dependent modulation of speech-induced auditory suppression for pitch-shifted voice feedback.语音诱导的听觉抑制对音高移位语音反馈的误差相关调制。
BMC Neurosci. 2011 Jun 6;12:54. doi: 10.1186/1471-2202-12-54.

运动想象控制语音合成脑-机接口时运动诱发的 N100 事件相关电位抑制。

Motor-Induced Suppression of the N100 Event-Related Potential During Motor Imagery Control of a Speech Synthesizer Brain-Computer Interface.

机构信息

Department of Speech-Language-Hearing: Sciences & Disorders, The University of Kansas, Lawrence.

出版信息

J Speech Lang Hear Res. 2019 Jul 15;62(7):2133-2140. doi: 10.1044/2019_JSLHR-S-MSC18-18-0198.

DOI:10.1044/2019_JSLHR-S-MSC18-18-0198
PMID:31306609
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6808362/
Abstract

Purpose Speech motor control relies on neural processes for generating sensory expectations using an efference copy mechanism to maintain accurate productions. The N100 auditory event-related potential (ERP) has been identified as a possible neural marker of the efference copy with a reduced amplitude during active listening while speaking when compared to passive listening. This study investigates N100 suppression while controlling a motor imagery speech synthesizer brain-computer interface (BCI) with instantaneous auditory feedback to determine whether similar mechanisms are used for monitoring BCI-based speech output that may both support BCI learning through existing speech motor networks and be used as a clinical marker for the speech network integrity in individuals without severe speech and physical impairments. Method The motor-induced N100 suppression is examined based on data from 10 participants who controlled a BCI speech synthesizer using limb motor imagery. We considered listening to auditory target stimuli (without motor imagery) in the BCI study as passive listening and listening to BCI-controlled speech output (with motor imagery) as active listening since audio output depends on imagined movements. The resulting ERP was assessed for statistical significance using a mixed-effects general linear model. Results Statistically significant N100 ERP amplitude differences were observed between active and passive listening during the BCI task. Post hoc analyses confirm the N100 amplitude was suppressed during active listening. Conclusion Observation of the N100 suppression suggests motor planning brain networks are active as participants control the BCI synthesizer, which may aid speech BCI mastery.

摘要

目的 言语运动控制依赖于神经过程,通过传出复制机制生成感觉预期,以维持准确的发音。已确定 N100 听觉事件相关电位(ERP)是传出复制的可能神经标志物,与被动聆听相比,在主动聆听时说话时振幅降低。本研究通过即时听觉反馈控制运动想象言语合成器脑机接口(BCI),调查 N100 抑制情况,以确定是否使用类似机制来监测基于 BCI 的言语输出,这既可以通过现有的言语运动网络支持 BCI 学习,也可以作为无严重言语和身体障碍个体的言语网络完整性的临床标志物。 方法 基于 10 名参与者的数据分析,检查运动引起的 N100 抑制,这些参与者使用肢体运动想象来控制 BCI 言语合成器。我们认为在 BCI 研究中聆听听觉目标刺激(无运动想象)为被动聆听,而聆听 BCI 控制的言语输出(有运动想象)为主动聆听,因为音频输出取决于想象的运动。使用混合效应广义线性模型评估 ERP 的统计学意义。 结果 在 BCI 任务期间,在主动聆听和被动聆听之间观察到统计学上显著的 N100 ERP 幅度差异。事后分析证实,在主动聆听期间,N100 幅度受到抑制。 结论 观察到 N100 抑制表明,参与者控制 BCI 合成器时,运动规划大脑网络处于活跃状态,这可能有助于掌握言语 BCI。