Novel Computational Analysis of Prosody in ASD and the Broad Autism Phenotype

自闭症谱系障碍和广泛自闭症表型韵律的新颖计算分析

• 批准号: 10113580
• 负责人: Molly C Losh
• 金额: $ 7.46万
• 依托单位: NORTHWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10113580
• 关键词: Acoustics; Address; Adopted; Affect; Affective; Age; Assessment tool; Behavioral; Biological; Biological Markers; Biology; Categories; Characteristics; Child; Clinical; Clinical assessments; Companions; Computational Linguistics; Computer Analysis; Computer Models; Data; Detection; Diagnostic; Emotions; Etiology; Family; Family Study; Frequencies; Genes; Genetic; Genetic Markers; Genetic Risk; Goals; Heterogeneity; Impairment; Individual; Intention; Intervention; Investigation; Language; Language Disorders; Link; Machine Learning; Measurable; Measures; Methods; Molecular Genetics; Outcome; Parents; Performance; Periodicity; Phenotype; Property; Reproducibility; Research; Sampling; Social Interaction; Speech; Speech Sound; Stress; Structure; Subgroup; System; Techniques; Training; Variant; Work; analytical tool; autism spectrum disorder; behavioral phenotyping; brain behavior; clinically significant; computerized tools; disorder risk; endophenotype; follow-up; improved; indexing; individuals with autism spectrum disorder; language impairment; novel; peer; predictive marker; relating to nervous system; response; skills; social; speech processing; symptomatology; tool; trait

Abstract Pragmatic (i.e., social) language impairments are a core feature of Autism Spectrum Disorder (ASD), and differences have also been observed more subtly in the Broad Autism Phenotype (BAP; a cluster of subclinical features related to ASD, which are believed to reflect genetic liability in clinically unaffected relatives). Prosody is a central component of pragmatics, which includes aspects of speech and language that modulate and enhance meaning at grammatical, pragmatic, and affective levels including stress and intonation, which are conveyed by changes in fundamental frequency, intensity, and rate. Atypical prosody in ASD has been identified as the most prominent feature that immediately identifies an individual with ASD as “odd” compared to typically developing peers, causing significant obstacles to social interaction and integration1-3. More subtle differences in prosody have also been observed among parents of individuals with ASD, and may serve as a key marker of ASD genetic risk, measurable in affected and unaffected individuals. Because speech samples may be easily obtained, identification of key prosodic profiles in ASD and profiles reflecting genetic liability to ASD, could have widespread implication as a biomarker for detection of ASD risk, and as a tool for assessment and interventions focused on this clinically significant feature of ASD. Limitations in current work pose significant barriers to the objective and efficient characterization of prosody, where current methods typically rely on subjective perceptual ratings which, though clinically valid, are difficult to obtain and apply objectively in treatment contexts, and are unfeasible for application with large samples. Moreover, without extensive training, perceptual rating methods are not adequately sensitive for capturing important variation and heterogeneity in ASD prosodic profiles, or identifying the often quite subtle yet biologically meaningful prosodic differences that may be observed in clinically unaffected relatives. These factors together impose substantial barriers to reproducibility, limit scalability, and render prosodic characterization unfeasible for use by clinicians. This project attempts to address these challenges by applying sophisticated computational modeling of extensive existing speech and language samples collected through a larger companion project (R01DC010191, PI: Losh), to characterize prosodic profiles in ASD and in parents. In Preliminary Data, we demonstrate evidence of distinct prosodic profiles of individuals with ASD and parents, along with relationships to broader pragmatic language abilities and neural processing of speech sounds in ASD and parents, supporting the goals of this project to apply sophisticated computational tools to speech data obtained across multiple contexts in order to 1) identify prosodic profiles that characterize ASD and the BAP in parents, and 2) examine how prosodic profiles relate to broader clinical-behavioral phenotypes, and aggregate within families, potentially contributing phenotypic signatures of clinically and etiologically more homogeneous subgroups.

抽象的 语用（即社交）语言障碍是自闭症谱系障碍 (ASD) 的核心特征，并且 在广泛自闭症表型（BAP；一组亚临床症状）中也观察到了更微妙的差异。 与 ASD 相关的特征，被认为反映了临床上未受影响的亲属的遗传倾向）。韵律 是语用学的核心组成部分，包括言语和语言的调节和语言方面 增强语法、语用和情感层面的意义，包括重音和语调，这些是 通过基频、强度和速率的变化来传达。自闭症谱系障碍 (ASD) 中的非典型韵律 被认为是最突出的特征，可以立即将患有自闭症谱系障碍的人识别为“奇怪”的人 对典型发展中的同龄人来说，对社交互动和融入造成重大障碍1-3。更微妙 在自闭症谱系障碍患者的父母中也观察到了韵律的差异，这可能可以作为一种 ASD 遗传风险的关键标志，可在受影响和未受影响的个体中进行测量。因为语音样本 可以很容易地获得，识别 ASD 中的关键韵律特征和反映遗传倾向的特征 ASD，作为检测 ASD 风险的生物标志物，以及作为一种工具，可能具有广泛的影响。 评估和干预措施的重点是自闭症谱系障碍的这一临床显着特征。当前工作的局限性 对韵律的客观和有效的表征构成了重大障碍，其中当前的方法 通常依赖于主观感知评级，尽管临床上有效，但很难获得和应用 在治疗环境中客观，并且不适合大样本应用。而且，不带 大量的训练、感知评级方法对于捕捉重要的变化不够敏感， ASD 韵律特征的异质性，或识别通常相当微妙但具有生物学意义的韵律 在临床上未受影响的亲属中可能观察到差异。这些因素共同影响了重大 再现性障碍，限制可扩展性，并使韵律特征无法被临床医生使用。 该项目试图通过应用复杂的计算模型来解决这些挑战 通过更大的配套项目收集的大量现有语音和语言样本 （R01DC010191，PI：Lesh），描述自闭症谱系障碍（ASD）和父母的韵律特征。在初步数据中，我们 证明自闭症患者和父母的独特韵律特征以及关系的证据 自闭症谱系障碍者和父母更广泛的语用语言能力和语音神经处理能力， 支持该项目的目标，将复杂的计算工具应用于跨领域获得的语音数据 多个上下文，以便 1) 识别表征 ASD 和父母 BAP 特征的韵律特征，以及 2) 检查韵律特征如何与更广泛的临床行为表型相关，并在家庭内聚合， 临床和病因学上更同质的亚组的潜在贡献表型特征。