High-resolution functional imaging of speech-induced sensory modulation

语音引起的感觉调制的高分辨率功能成像

• 批准号: 10802563
• 负责人: Jason W Bohland
• 金额: $ 45.88万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-18 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10802563
• 关键词: Acceleration; Acoustics; Adult; Anatomy; Area; Attenuated; Auditory; Auditory area; Benchmarking; Biological Models; Brain; Brain Mapping; Brain region; Cell Nucleus; Cerebellar Cortex; Cerebellum; Code; Complex; Computer Models; Data; Diagnosis; Electrocorticogram; Electroencephalography; Electrophysiology (science); Evoked Potentials; Experimental Designs; Feedback; Functional Imaging; Functional Magnetic Resonance Imaging; Future; GRB10 gene; Goals; Human; Individual; Influentials; Intervention; Investigation; Knowledge; Learning; Lesion; Link; Lobule; Magnetic Resonance Imaging; Magnetoencephalography; Maps; Measurement; Measures; Mediating; Methods; Modeling; Modernization; Monitor; Motor; Motor Cortex; Motor output; Movement; Nature; Neurobiology; Output; Participant; Pathway interactions; Pattern; Persons; Phonetics; Primates; Process; Production; Readiness; Research; Resolution; Role; Sampling; Sensory; Series; Signal Transduction; Specificity; Speech; Speech Disorders; Structure of superior temporal sulcus; Stuttering; Superior temporal gyrus; System; Techniques; Testing; Thalamic structure; Uncertainty; auditory feedback; cerebellar lesion; design; experimental study; improved; individual variation; insight; interest; lens; motor control; motor learning; neural; neuroimaging; non-verbal; personalized approach; phonology; predictive modeling; recruit; response; sensory cortex; sensory feedback; sensory system; sound; theories; tool

PROJECT SUMMARY / ABSTRACT The overall goal of this project is to test and refine a neurobiological systems model of speech-induced sensory modulation (SISM). Previous studies used magnetoencephalography (MEG) and electroencephalography (EEG) to reveal that auditory cortical responses evoked when speaking are reduced compared to passive listening, a phenomenon known as speaking-induced suppression (SIS). This effect has been proposed to reflect the action of learned forward models that predict sensory consequences of speech movements. While EEG/MEG studies of SIS have provided important insights, these methods have limited anatomical precision. For this reason, the auditory regions modulated by forward model predictions in speech, and the circuits that mediate them, remain relatively poorly understood. To close this knowledge gap, this project uses 7T fMRI to measure brainwide activity at exquisite resolution while participants complete a series of related auditory-motor tasks across multiple sessions. Guided by contemporary models of speech production, we hypothesize that three functional circuits link frontal speech planning areas with superior temporal auditory areas via cortical and trans-cerebellar pathways, providing sensory predictions at different levels of representation. In Aim 1, one EEG and three fMRI experiments will be used to map the sensory cortical areas modulated by self-generated speech. These studies will define subject-specific regions-of-interest (ROIs) that differentially respond to overt speech vs. passive listening to oneself or another speaker producing the same syllables or sentences. Multivariate encoding models test hypotheses about the speech features represented in these ROIs. In the same speakers, we will determine the extent and specificity of modulations in these ROIs during movement planning, prior to motor output. Aim 2 tests how these ROIs participate in error monitoring. Two fMRI experiments are designed to test hypotheses about responses to auditory errors that are either (1) “low-level” acoustic-phonetic errors induced by unexpected shifts in auditory feedback, or (2) “high-level” sound substitution errors elicited during a phonological error priming task. Because Aim 2 is carried out in the same speakers as Aim 1, within-subject comparisons will enable high- resolution individual-specific models and interpretations across observed effects. In Aim 3, we will determine the role of the cerebellum (CB) in implementing learned forward models that drive SISM. Individuals with cerebellar lesions and controls will be recruited to test the hypothesis that the CB is critical in learning predictive models for speech. In these participants, and those tested in Aims 1 and 2, 7T fMRI will measure neural activity changes during a speech motor adaptation task and a non-vocal auditory-motor learning task. Individuals with lesions in Lobule VI are predicted to show reduced learning, reduced SISM, and reduced associations between CB and auditory cortical activity. Together these studies will accelerate understanding of sensory-motor interactions in speech through in-depth analysis of individual brains, enable the refinement of detailed neurocomputational models, and set the stage for precision approaches to diagnosis and intervention in speech disorders.

项目摘要 /摘要 该项目的总体目标是测试和完善语音感官的神经生物学系统模型 调制（SISM）。先前的研究使用磁脑电图（MEG）和脑电图（EEG） 为了揭示与被动聆听相比，说话减少时唤起的听觉皮质反应， 现象称为说话引起的抑制（SIS）。已经提出了这种效果来反映行动 博学的前向模型可以预测语音运动的感官后果。脑电图/梅格研究 SI提供了重要的见解，这些方法的解剖学精度有限。因此， 听觉区域是由语音中的远期模型预测调节的，以及调解它们的电路 相对较少的理解。为了缩小这一知识差距，该项目使用7T fMRI来测量整个活动 通过独家分辨率，参与者完成了一系列相关的听觉运动任务 会议。在当代语音生产模型的指导下，我们假设三个功能电路 通过皮质和跨性别的界面和临时听觉区域将额叶语音规划区域与优越的临时听觉区域联系起来 途径，提供不同表示级别的感觉预测。在AIM 1中，一个脑电图和三个fMRI 实验将用于绘制由自我生成的语音调节的感觉皮质区域。这些研究 将定义特定主题的利益区域（ROI），对公开语音与被动反应不同 倾听自己或另一个发言人产生相同的音节或句子。多元编码模型 关于这些ROI中代表的语音特征的测试假设。在同一扬声器中，我们将确定 在运动计划之前，在运动计划期间，调制的程度和特异性在电动机输出之前。目标2 测试这些ROI如何参与错误监视。两个fMRI实验旨在检验假设 关于对听觉错误的响应（1）意外引起的“低级”声音错误 听觉反馈的变化，或（2）在语音错误启动期间引起的“高级”声音替代错误 任务。由于AIM 2与AIM 1同一扬声器进行，因此受试者内部比较将使高 分辨率跨观察到的效果的个人特定模型和解释。在AIM 3中，我们将确定 小脑（CB）在实施驱动sism的远期模型中的作用。小脑的人 病变和控制将被招募，以检验以下假设：CB对于学习预测模型至关重要 演讲。在这些参与者中，以及在目标1和2中测试的参与者，7T fMRI将测量神经活动的变化 在语音运动适应任务和非声音听觉运动任务中。有腿的人 预计小叶VI显示出减少的学习，SISM降低以及CB与CB之间的关联减少 听觉皮质活动。这些研究将加速对感觉运动相互作用的理解 通过对单个大脑进行深入分析的语音，使详细的神经计算能够完善 模型，并为诊断和言语干预的精确方法奠定了基础。