Behavioral and Neural Measures of Spoken Word Recognition in Late Language Emergence

晚期语言出现中口语识别的行为和神经测量

• 批准号: 10437317
• 负责人: Elizabeth Simmons
• 金额: $ 35.58万
• 依托单位: SACRED HEART UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10437317
• 关键词: Address; Adolescence; Age; Age-Months; Attenuated; Behavioral; Biological Markers; Child; Chronic; Clinical; Complement; Comprehension; Control Groups; Data; Development; Developmental Delay Disorders; Diagnosis; Disease; Early Intervention; Electroencephalography; Endowment; Etiology; Event-Related Potentials; Foundations; Future; Grain; Growth; Heterogeneity; Impairment; Individual Differences; Intervention; Intervention Studies; Knowledge; Laboratories; Language; Language Development; Language Development Disorders; Language Disorders; Machine Learning; Measurement; Measures; Motor; Outcome; Participant; Phenotype; Problem Solving; Process; Production; Public Health; Research; Research Proposals; Resources; Risk; Sampling; School-Age Population; Semantics; Sensory; Signal Transduction; Speech; Speed; Stimulus; Structure; Time; Toddler; Training; Variant; Visual; Vocabulary; Word Processing; Work; autism spectrum disorder; behavioral phenotyping; emerging adult; experimental study; improved; individual variation; insight; language comprehension; language disorder diagnosis; language impairment; language outcome; language processing; lexical; lexical processing; literacy; machine learning algorithm; movie; multimodality; neural correlate; novel; peer; phonology; prospective; reduce symptoms; relating to nervous system; response; social; sound; success; support vector machine; trait; visual tracking

ABSTRACT Toddlers with late language emergence (LLE), or late talkers (LTs), are 18-35 month-olds with a limited spoken vocabulary, but average non-linguistic abilities and no overt sensory impairments or other developmental delays such as autism spectrum disorder (Collisson, 2016; Paul & Jennings, 1992). Approximately 15% of toddlers meet LLE criteria (Singleton, 2018; Paul, 1992) and are at elevated risk for persistent, lifelong language and literacy deficits that result in poor social, academic and vocational outcomes (Paul, 1993; Rescorla, 2009; Singleton, 2018). Upwards of 16% of LTs will prospectively be diagnosed with a spoken and/or written language disorder at age 9 (Paul, Murray, Clancy, & Andrews, 1997) while the majority of LTs retain suboptimal language functioning through early adulthood (Rescorla, 2002; Singleton, 2018). The proposed research seeks to (1) identify early behavioral and neural markers of chronic impact in order to optimally allocate scarce early intervention resources, and (2) examine the variation and distribution of behavioral phenotypes which will provide the foundation for more focused and targeted forms of interventions for LTs with a range of clinical and subclinical language outcomes. The project will complement prior work on LLE focused on language production by evaluating the fine- grained timecourse of spoken word recognition (SWR) in LTs and two control groups (typically developing age- matched and language-matched peers) using behavioral (eye tracking) and neural (electroencephalography) measurements. All participants will complete comprehensive clinical characterization including assessments of language and non-linguistic functioning. In Experiment 1, participants will be trained on a simple selection task using eight familiar words that overlap phonologically (e.g., at onset, BUNNY-BUBBLES, at offset, KITTEN- MITTEN) and semantically (e.g., BUNNY-KITTEN). Eye tracking will be used to estimate group and individual differences in lexical activation and competition over time in the selection task. In Experiment 2, neural responses will be recorded in a passive listening paradigm, using EEG, as participants view a silent movie while the familiar words from Experiment 1 are repeated many times. We will train a machine-learning algorithm (support vector machine, or SVM) to decode the full EEG response to specific words for each toddler. Group and individual differences in the relative success of the SVM may reflect the consistency and fidelity of neural responses. ERP (event-related potential) analysis will also be used to examine group and individual differences in mean responses to the spoken words. Group and individual differences in eye tracking, EEG and/or ERP measures will yield new insights into the language processing abilities of LTs and will provide a basis for future work aimed at identifying those LTs at greatest risk for poor outcomes.

抽象的 具有后期语言出现（LLE）或晚讲话者（LTS）的幼儿是18-35个月大的孩子 口语词汇，但平均非语言能力，没有明显的感觉障碍或其他发育 诸如自闭症谱系障碍之类的延迟（Collisson，2016； Paul＆Jennings，1992）。约15％ 幼儿符合LLE标准（Singleton，2018； Paul，1992），并且持续，终身语言的风险较高 以及导致社会，学术和职业成果不佳的识字赤字（Paul，1993； Rescorla，2009年； Singleton，2018年）。超过16％的LTS将被前瞻性地诊断出使用语言和/或书面语言 9岁时的障碍（Paul，Murray，Clancy和Andrews，1997年），而大多数LTS保留了次优的语言 在成年初期运作（Rescorla，2002; Singleton，2018）。拟议的研究试图（1） 确定慢性影响的早期行为和神经标记，以便尽早分配稀缺 干预资源以及（2）检查将提供的行为表型的变化和分布 具有一系列临床和亚临床的LT的更集中和针对性的干预措施的基础 语言结果。 该项目将通过评估罚款 - LTS和两个对照组中口语识别（SWR）的语言识别时间（通常是发展年龄） 使用行为（眼科跟踪）和神经（脑电图）匹配和语言匹配的同伴） 测量。所有参与者将完成全面的临床特征，包括评估 语言和非语言功能。在实验1中，将对参与者进行简单选择任务的培训 使用八个熟悉的单词，这些单词在语音学上重叠（例如，在一开始，兔子bubbles，偏移时，小猫 - 手套）和语义（例如兔子小说）。眼睛跟踪将用于估计组和个人 随着时间的推移，选择任务的词汇激活和竞争的差异。在实验2中，神经反应 参与者在熟悉的时候观看无声电影时，将在被动听力范式中记录在被动的听力范式中 实验1中的单词多次重复。我们将训练一种机器学习算法（支持向量 机器或SVM）解码每个幼儿对特定单词的完整脑电图响应。团体和个人 SVM相对成功的差异可能反映了神经反应的一致性和保真度。 ERP （与事件相关的潜力）也将用于检查平均值的群体和个体差异 对口语的回应。小组和个体跟踪，脑电图和/或ERP度量的差异 将对LTS的语言处理能力产生新的见解，并将为未来的工作提供基础 在确定那些有差预后风险的LT。