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 这个项目的总体目标是测试和提炼一个言语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(EEG)。 为了揭示与被动倾听相比，说话时诱发的听觉皮质反应减少，一项 被称为言语诱导抑制(SIS)的现象。这一效果已被提出以反映行动 预测言语运动的感觉后果的学习前向模型。同时进行脑电/脑磁图研究 提供了重要的见解，但这些方法的解剖学精度有限。出于这个原因， 语音中受前向模型预测调制的听觉区域和调节它们的电路仍然存在 相对较少被人理解。为了缩小这一知识差距，该项目使用7T功能磁共振成像来测量全脑活动 以精致的分辨率完成一系列相关的听觉-运动任务 会话。在当代语音产生模型的指导下，我们假设有三个功能回路 通过皮质和经小脑将额叶语言规划区与优势的颞叶听区联系起来 通路，在不同的表征水平上提供感官预测。在目标1中，一个EEG和三个fMRI 实验将被用来绘制由自我产生的语音调制的感觉皮层区域。这些研究 将定义特定于对象的感兴趣区域(ROI)，这些ROI对公开的语音和被动的语音做出不同的反应 听自己或另一个说话者说出相同的音节或句子。多变量编码模型 测试关于这些ROI中表示的语音特征的假设。在同一个演讲者中，我们将确定 在运动计划期间，在运动输出之前，这些感兴趣区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。设计了两个功能磁共振成像实验来验证假设。 关于对以下两种听觉错误的反应：(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起的“高水平”声音替代错误 任务。由于目标2与目标1是在相同的演讲者中进行的，因此受试者内部的比较将使 解决个人特定的模型和对观察到的影响的解释。在目标3中，我们将确定 小脑(CB)在实现驱动SISM的学习前向模型中的作用。有小脑症状的个体 将招募病变和对照来检验CB在学习预测模型中的关键的假设 演讲。在这些参与者中，以及那些在AIMS 1和AIMS 2中进行测试的人，7T fMRI将测量神经活动的变化 在言语运动适应任务和非发声听觉-运动学习任务中。有皮损的个人 小叶VI被预测显示学习减少，SISM减少，CB和Cb之间的联系减少 听觉皮质活动。总之，这些研究将促进对感觉-运动相互作用的理解 语音通过对个体大脑的深入分析，使精细的神经计算成为可能 模型，并为语音障碍的精确诊断和干预方法奠定了基础。