Sequencing and Initiation in Speech Production

语音生成中的排序和启动

• 批准号: 8960716
• 负责人: FRANK H GUENTHER
• 金额: $ 36.11万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8960716
• 关键词: Accounting; Achievement; Adult; Adult Stuttering; Adverse effects; Affect; Age; Basal Ganglia; Behavior; Behavioral Model; Benchmarking; Brain; Characteristics; Child; Cluster Analysis; Complex; Computer Simulation; Cues; Data; Data Set; Developmental Stuttering; Diffusion Magnetic Resonance Imaging; Disease; Disease model; Functional Magnetic Resonance Imaging; Gestures; Goals; Impairment; Left; Measures; Modeling; Modification; Motor; Movement; Neurophysiology - biologic function; Occupational; Outcomes Research; Personal Satisfaction; Persons; Prevalence; Process; Production; Rest; Severities; Specificity; Speech; Speech Sound; Study models; Stuttering; System; Testing; Time; Tornadoes; United States; Weather; Work; atmospheric conditions; auditory feedback; base; design; effective therapy; frontal lobe; gray matter; improved; neural patterning; neuroimaging; neuromechanism; novel; phonology; programs; psychologic; public health relevance; relating to nervous system; response; simulation; social; sound; speech processing; success; therapy development; white matter

 DESCRIPTION (provided by applicant): The overall goal of this project is to develop and test a detailed neural and computational account of the brain mechanisms underlying speech motor sequence planning and their breakdown in stuttering. Persistent developmental stuttering affects more than three million people in the United States, and it can have profound adverse effects on social, psychological, and occupational well-being. Despite its world-wide prevalence and negative impact, stuttering has resisted explanation and effective treatment. This project investigates the hypothesis that stuttering is caused by a network-level neural disturbance rather than a disturbance in a single neural region, and the functional result of this disturbance is an impaired ability to use phonological and sensorimotor contextual cues to select and initiate motor programs for upcoming speech gestures. This hypothesis will be tested using a highly integrated combination of neuroimaging and modeling studies organized around the GODIVA neurocomputational model of speech motor sequencing. Study 1 involves the use perturbations of auditory feedback during speech in a functional MRI study of the brain mechanisms underlying speech timing adjustments based on sensorimotor context. Comparison of brain activities from AWS to fluent controls will identify the neural deficits underlying an impaired ability of adults who stutter (AWS) to adjust speech motor timing in response to auditory feedback. In Study 2, repetition suppression functional magnetic resonance imaging will be used to (i) refine our understanding of phonological representations underlying speech production in fluent adults, and (ii) identify anomalies in the phonological representations of AWS that may degrade the speech sequencing system's ability to recognize the proper context for generating the next speech gesture. Study 3 utilizes a large structural and functional neuroimaging dataset from children who stutter (CWS), AWS, and matched controls to disentangle primary neural deficits underlying stuttering from secondary deficits and compensatory mechanisms, and to identify potential sub-types of stuttering involving different neural anomalies. Study 4 is a modeling project that synthesizes the findings from Studies 1- 3 into a detailed neurocomputational account of speech motor sequencing in the normal brain and its breakdown in stuttering. Key benchmarks of success include the ability to replicate anomalous movement timing patterns and neural activity in AWS and CWS compared to fluent speakers. The resulting neurocomputational model of stuttering will constitute a significant milestone in the centuries-old effort to understand this perplexing disorder and will pave the way for designing and testing novel treatments that are aimed squarely at the primary neural deficits.

 描述（由申请人提供）：该项目的总体目标是开发和测试关于语音运动序列规划及其在口吃​​中的分解的大脑机制的详细神经和计算说明。在美国，持续性发育性口吃影响着超过 300 万人，它会对社会、心理和职业健康产生深远的不利影响。尽管口吃在世界范围内普遍存在并产生负面影响，但它一直无法得到解释和有效的治疗。该项目研究了这样的假设：口吃是由网络级神经紊乱而不是单个神经区域的紊乱引起的，这种紊乱的功能结果是使用语音和感觉运动上下文线索来选择和启动即将到来的语音手势的运动程序的能力受损。这一假设将通过高度集成的神经影像学和建模研究组合进行测试，这些研究围绕语音运动测序的 GODIVA 神经计算模型组织。研究 1 涉及在功能性 MRI 研究中使用言语期间听觉反馈的扰动，研究基于感觉运动背景的言语时序调整的大脑机制。将 AWS 与流利对照的大脑活动进行比较，将确定口吃成年人 (AWS) 根据听觉反馈调整言语运动时序的能力受损背后的神经缺陷。在研究 2 中，重复抑制功能磁共振成像将用于 (i) 完善我们对流利成人语音生成背后的语音表征的理解，以及 (ii) 识别 AWS 语音表征中的异常，这些异常可能会降低语音排序系统识别生成下一个语音手势的正确上下文的能力。研究 3 利用来自口吃儿童 (CWS)、AWS 和匹配对照的大型结构和功能神经影像数据集，将口吃背后的原发性神经缺陷与继发性缺陷和补偿机制区分开来，并识别涉及不同神经异常的潜在口吃亚型。研究 4 是一个建模项目，它将研究 1-3 的研究结果综合为正常大脑中言语运动序列及其在口吃​​中的分解的详细神经计算说明。成功的关键基准包括与流利的演讲者相比，在 AWS 和 CWS 中复制异常运动计时模式和神经活动的能力。由此产生的口吃神经计算模型将成为理解这种令人困惑的疾病的数百年努力中的一个重要里程碑，并将为设计和测试直接针对原发性神经缺陷的新疗法铺平道路。