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.

项目概要/摘要 该项目的总体目标是测试和完善语音诱导感觉的神经生物学系统模型 调制（SISM）。先前的研究使用脑磁图（MEG）和脑电图（EEG） 为了揭示与被动倾听相比，说话时引起的听觉皮层反应减少了， 这种现象称为言语诱导抑制（SIS）。提出这种效果是为了反映行动 预测言语运动的感官后果的学习前向模型。当脑电图/脑磁图研究 SIS 提供了重要的见解，但这些方法的解剖精度有限。为此， 由语音中的前向模型预测调制的听觉区域以及调解它们的电路仍然存在 相对了解较少。为了弥补这一知识差距，该项目使用 7T fMRI 来测量全脑活动 以精致的分辨率，同时参与者完成一系列跨多个相关的听觉运动任务 会议。在当代语音产生模型的指导下，我们假设三个功能电路 通过皮质和跨小脑将额叶言语规划区与上颞听觉区连接起来 路径，提供不同表征水平的感官预测。在目标 1 中，一项脑电图和三项功能磁共振成像 实验将用于绘制由自生成语音调制的感觉皮层区域。这些研究 将定义特定主题的兴趣区域 (ROI)，这些区域对公开言语和被动言语的反应不同 听自己或另一个说话者发出相同的音节或句子。多元编码模型 测试有关这些 ROI 中代表的语音特征的假设。在相同的扬声器中，我们将确定 在运动计划期间，在运动输出之前，这些 ROI 中调制的程度和特异性。目标2 测试这些 ROI 如何参与错误监控。两个功能磁共振成像实验旨在检验假设 关于对听觉错误的反应，这些错误是（1）由意外引起的“低级”声学语音错误 听觉反馈的变化，或（2）在语音错误启动过程中引发的“高水平”声音替代错误 任务。因为目标 2 是在与目标 1 相同的扬声器中进行的，所以受试者内比较将能够实现高 解决观察到的效应的个体特定模型和解释。在目标 3 中，我们将确定 小脑 (CB) 在实施驱动 SISM 的学习前向模型中的作用。有小脑的人 将招募病变和对照来测试 CB 在学习预测模型中至关重要的假设 演讲。在这些参与者以及目标 1 和 2 中测试的参与者中，7T fMRI 将测量神经活动变化 在言语运动适应任务和非言语听觉运动学习任务期间。患有病变的个体 预计 VI 小叶会表现出学习能力下降、SISM 下降以及 CB 和 CB 之间的关联减少 听觉皮层活动。这些研究将共同​​加速对感觉-运动相互作用的理解 通过对个体大脑的深入分析，能够细化详细的神经计算 模型，并为言语障碍的精确诊断和干预方法奠定了基础。