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.

摘要 务实（即，社会）语言障碍是自闭症谱系障碍（ASD）的核心特征， 在广泛自闭症表型（BAP;一组亚临床自闭症）中也观察到了更微妙的差异。 与ASD相关的特征，这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，包括言语和语言的各个方面， 在语法、语用和情感层面上增强意义，包括重音和语调， 通过基频、强度和速率的变化来传达。ASD中的非典型韵律一直是 被认为是最突出的特征，可以立即将ASD患者识别为“奇怪”， 通常发展同龄人，造成社会交往和整合的重大障碍1 -3。更微妙 在ASD患者的父母中也观察到了韵律的差异，这可能是一种 ASD遗传风险的关键标志物，可在受影响和未受影响的个体中测量。因为语音样本 可以很容易地获得，识别ASD中的关键韵律谱和反映遗传易感性的谱， ASD，可能作为检测ASD风险的生物标志物，并作为一种工具， 评估和干预集中在ASD的这一临床显著特征上。当前工作的局限性 对韵律的客观和有效表征构成重大障碍，其中当前方法 典型地依赖于主观的感知等级，虽然临床上有效，但是难以获得和应用 客观地在治疗环境中，并且对于大样本的应用是不可行的。而且没有 广泛的训练，感知评级方法对于捕捉重要的变化不足够敏感， ASD韵律特征的异质性，或者识别通常相当微妙但具有生物学意义的韵律特征。 在临床上未受影响的亲属中可能观察到的差异。这些因素共同造成了巨大的 再现性的障碍、限制了可缩放性，并且使得韵律表征对于临床医生的使用是不可行的。 该项目试图通过应用复杂的计算模型来解决这些挑战， 通过一个更大的配套项目收集的广泛的现有语音和语言样本 （R 01 DC 010191，PI：Losh），以表征ASD和父母的韵律特征。在初步数据中，我们 证明了ASD患者和父母的不同韵律特征的证据，沿着关系 更广泛的语用语言能力和ASD及其父母对语音的神经处理， 支持这个项目的目标，将复杂的计算工具应用于从 多个上下文，以便1）识别表征父母中的ASD和BAP的韵律简档，以及2） 研究韵律特征如何与更广泛的临床行为表型相关，并在家庭内聚集， 可能有助于临床和病因学上更同质的亚组的表型特征。