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.

项目总结/摘要 这个项目的总体目标是测试和完善一个神经生物学系统模型的言语诱导的感觉 调制（SISM）。以前的研究使用脑磁图（MEG）和脑电图（EEG） 为了揭示说话时诱发的听觉皮层反应与被动倾听相比有所减少， 这种现象被称为说话诱发抑制（SIS）。这种效应被提出来反映 学习的前向模型，预测言语运动的感官后果。虽然EEG/MEG研究 SIS的方法提供了重要的见解，但这些方法的解剖精度有限。为此该 由语音中的前向模型预测所调制的听觉区域，以及介导它们的回路， 相对来说，了解得很少。为了缩小这一知识差距，该项目使用7 T功能磁共振成像来测量全脑活动 当参与者完成一系列相关的运动任务时， sessions.在当代言语产生模型的指导下，我们假设三个功能回路 通过皮层和经小脑连接额叶言语计划区和上级颞听觉区 通路，提供不同层次的代表性的感官预测。在目标1中，一个EEG和三个fMRI 实验将被用来映射由自发语音调制的感觉皮层区域。这些研究 将定义特定于主题的感兴趣区域（ROI），这些区域对显性语音和被动语音有不同的响应 听自己或另一个说话者发出同样的音节或句子。多元编码模型 测试关于这些ROI中表示的语音特征的假设。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。目的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 任务由于目标2是在与目标1相同的说话者中进行的，因此受试者内的比较将使高- 分辨率个体特异性模型和对观察到的效应的解释。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。患有小脑的人 将招募病变和对照，以检验CB在学习预测模型中至关重要的假设， 演讲在这些参与者中，以及在目标1和2中测试的参与者中，7 T fMRI将测量神经活动变化 在言语运动适应任务和非发声运动-运动学习任务期间。有病变的个体 预计小叶VI显示出减少的学习，减少的SISM，以及CB和 听觉皮层活动这些研究将加速对感觉-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 模型，并为精确的方法来诊断和干预语言障碍奠定了基础。