Assessment of speech- and fine-motor coordination and their link to language in children with autism spectrum disorder

自闭症谱系障碍儿童的言语和精细运动协调及其与语言的联系的评估

• 批准号: 10381787
• 负责人: Tanya Talkar
• 金额: $ 3.38万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2023-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10381787
• 关键词: Abnormal coordination; Acoustics; Affect; Algorithms; Articulators; Biological Markers; Child; Clinical; Clinical assessments; Cognitive; Communication; Complex; Coupling; Dependence; Discrimination; Enrollment; Evaluation; Eye Movements; Face; Future; Goals; Handwriting; Individual; Intervention; Language; Larynx; Link; Machine Learning; Major Depressive Disorder; Measures; Modality; Modeling; Monitor; Motor; Motor Skills; Movement; Muscle; Neurodevelopmental Disorder; Outcome Assessment; Parkinson Disease; Pattern; Physiological; Pilot Projects; Population; Production; Protocols documentation; Proxy; Research; Series; Severities; Shapes; Speech; Structure; System; Techniques; Time; Training; United States; Work; autism spectrum disorder; autistic children; behavior measurement; clinical predictors; improved; individuals with autism spectrum disorder; insight; language outcome; mild traumatic brain injury; motor impairment; nervous system disorder; novel; oculomotor; respiratory; sensorimotor system; social; visual tracking

PROJECT SUMMARY Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder associated with motor difficulties in speech production and fine-motor tasks. Assessments of motor impairments, however, can be subjective and miss subtle and specific abnormalities. Therefore, there is a need to develop objective measures for clinicians to assess and understand speech- and fine-motor impairments in individuals with ASD. In addition, recent research suggests that difficulties with speech production, fine-motor, and oculo-motor tasks may contribute to language difficulties in ASD. The purpose of this project is to develop objective measures of speech- and fine-motor coordination in children with ASD, and to characterize the relationship between motor modalities and expressive language in ASD using these measures. We will focus on three speech subsystems: articulatory, laryngeal, and respiratory, as well as handwriting and eye movement. In a pilot study we conducted at the Lurie Center for Autism, we utilized novel coordination features developed in our lab to highlight lower complexity of coordination, or higher coupling, between and within speech subsystems in highly verbal children with ASD as compared to neurotypical controls. The analyses also indicated lower complexity of coordination during handwriting in children with ASD, suggesting there may be similar underlying mechanisms across these motor systems. In the proposed project, we will extend upon these promising results, evaluating measures of motor coordination using low-level features derived from speech, handwriting, and eye movement tasks completed by children with ASD and neurotypical controls. We will employ acoustic-to-articulatory inversion techniques to extract more physiologically accurate vocal tract articulator movements and coordination. Aim 1 uses measures of coordination to characterize the complexity of speech- and fine-motor coordination in children with ASD. We will also determine the features which provide the highest discriminatory ability between children with ASD and neurotypical controls using machine learning models. We expect that identification of patterns of complexity and important discriminatory features will provide a better understanding of the dependencies across and within motor subsystems, which could be used for objective assessment and tracking of motor difficulties in ASD. Aim 2 characterizes the relationship between speech- and fine-motor skills and expressive language ability. We will evaluate correlations and regressions between measures of motor coordination and scores on assessments of expressive language. We believe that motor tasks and features which show high correlations with evaluations of language ability will provide further insight into how motor modalities are associated with language difficulties in ASD. In summary, this proposal aims to quantify and understand speech- and fine-motor coordination challenges in ASD using objective measures of motor coordination, and aims to characterize the relationship between speech- and fine- motor subsystems and expressive language in ASD. This project works towards our long-term goal of developing a platform to assess, understand, and track motor and communication challenges in children with ASD.

项目概要 自闭症谱系障碍 (ASD) 是一种与言语运动困难相关的神经发育障碍 生产和精细运动任务。然而，对运动障碍的评估可能是主观的，并且可能会遗漏细微之处 以及具体的异常情况。因此，有必要制定客观的措施供临床医生评估和评估。 了解自闭症谱系障碍患者的言语和精细运动障碍。此外，最近的研究表明 言语产生、精细运动和眼动任务的困难可能会导致语言困难 在自闭症谱系障碍中。该项目的目的是开发言语和精细运动协调的客观测量方法 患有 ASD 的儿童，并描述运动方式和表达性语言之间的关系 ASD 使用这些措施。我们将重点关注三个语音子系统：发音、喉部和呼吸， 以及笔迹和眼球运动。在我们在卢里自闭症中心进行的一项试点研究中，我们 利用我们实验室开发的新颖的协调功能来突出协调的较低复杂性或更高的复杂性 与神经正常儿童相比，患有自闭症谱系障碍（ASD）的高度言语儿童的言语子系统之间和内部的耦合 控制。分析还表明，患有自闭症谱系障碍 (ASD) 的儿童在书写过程中的协调复杂性较低， 表明这些运动系统可能存在类似的潜在机制。在拟议的项目中， 我们将扩展这些有希望的结果，使用低级特征评估运动协调的措施 源自自闭症谱系障碍 (ASD) 和神经正常儿童完成的言语、手写和眼动任务 控制。我们将采用声学到发音反转技术来提取更符合生理学的准确信息 声道发音器官的运动和协调。目标 1 使用协调措施来描述 自闭症儿童言语和精细运动协调的复杂性。我们还将确定功能 它提供了 ASD 儿童和神经正常对照儿童之间最高的辨别能力，使用 机器学习模型。我们期望识别出复杂性和重要歧视性的模式 功能将有助于更好地理解电机子系统之间和内部的依赖关系，这 可用于客观评估和跟踪 ASD 运动困难。目标 2 的特点是 言语和精细运动技能与语言表达能力之间的关系。我们将评估相关性 以及运动协调测量与表达语言评估分数之间的回归。 我们相信，与语言能力评估高度相关的运动任务和特征将 进一步深入了解运动方式与自闭症谱系障碍（ASD）语言困难之间的关系。总之， 该提案旨在量化和理解自闭症谱系障碍 (ASD) 中的言语和精细运动协调挑战 运动协调的客观测量，旨在表征言语和精细之间的关系 ASD 中的运动子系统和表达语言。该项目致力于实现我们发展的长期目标 一个评估、理解和跟踪自闭症儿童运动和沟通挑战的平台。