The Influence of Morphosyntactic Network Complexity on Typical and Atypical Language Learning

形态句法网络复杂性对典型和非典型语言学习的影响

• 批准号: 10372204
• 负责人: Roger Beaty
• 金额: $ 20.06万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10372204
• 关键词: 2 year old; Address; Adult; Architecture; Area; Blueberries; Child; Child Language; Childhood; Complex; Dependence; Development; Diagnosis; Education; Employment; Environment; Exhibits; Exposure to; Family; Frequencies; Human; Impairment; Individual; Instinct; Intervention; Knowledge; Language; Language Development; Language Development Disorders; Language Disorders; Learning; Linguistics; Link; Measures; Methods; Morphology; Natural Language Processing; Output; Participant; Pathway Analysis; Pattern; Population; Prevalence; Process; Production; Property; Raspberries; Records; Research; Role; Sampling; Science; Semantics; Series; Signal Transduction; Speech; Strawberries; Structure; System; Testing; Therapeutic Intervention; Toddler; Work; aged; design; early childhood; educational atmosphere; experimental study; flexibility; indexing; innovation; kindergarten; language impairment; natural language; network architecture; phrases; skills; statistics; syntax; therapeutic development; tool; young adult

Project Summary The proposed project details an innovative line of research that draws on advanced tools from the field of network science to elucidate typical and atypical language learning mechanisms in adults. Network analysis of natural language has revealed a number of global structural patterns emerging from relationships (used to construct network edges) between words (used as network nodes). Informed by the naturally-occurring network architecture of real-world languages, we will construct miniature artificial languages that display emergent properties of existing language systems and measure the extent to which these languages are learned by adults with typical development (TD) and those with developmental language disorder (DLD) (Aim 1). Given that DLD is often associated with deficits in processing and producing complex morphosyntax, we will concentrate on networks in which edges between words represent either their co-occurrence in a sentence or overlap in morphological family (e.g., eater, eating). In Aim 2, we will examine whether language learning deficits in adults with DLD might be recast as a hyperfocus on local-level information (i.e., “oddball” structures or individual word frequency) at the expense of the broader architecture of the language learning environment. To strengthen links between deficits in language learning and expressive language, Aim 3 calls for the network analysis of elicited speech samples to reveal whether individuals less sensitive to complexity in learning might also display reduced complexity in their language output. Of individuals diagnosed with receptive and expressive language disorder in childhood, the vast majority continue to struggle with language impairment in adulthood. Despite a pressing need for expansion of adult-oriented language interventions, characterization of the full scope of deficits in individuals with DLD, in addition to their language learning mechanisms beyond childhood, is an understudied area.

项目摘要 拟议的项目详细介绍了一个创新的研究路线，借鉴了网络领域的先进工具， 科学阐明成人的典型和非典型语言学习机制。自然资源网络分析 语言揭示了一些从关系中出现的全球结构模式（用于构建 网络边缘）之间的单词（用作网络节点）。由自然发生的网络提供信息 我们将构建微型人工语言， 现有语言系统的特性，并衡量成年人学习这些语言的程度 有典型发展（TD）及有发展性语言障碍（DLD）的人士（目的1）。鉴于DLD 通常与处理和产生复杂形态句法的缺陷有关，我们将专注于 词与词之间的边表示它们在句子中的共同出现或在句子中的重叠。 形态学家族（例如，吃，吃）。在目标2中，我们将研究成年人的语言学习缺陷是否 DLD可能被重新塑造为对本地级信息的超关注（即，“古怪”结构或单个单词 频率），以牺牲语言学习环境的更广泛架构为代价。加强联系 在语言学习和表达语言的缺陷之间，目标3要求对引发的网络分析。 语音样本，以揭示是否个人不敏感的复杂性，在学习也可能显示减少 语言输出的复杂性。被诊断为接受性和表达性语言障碍的个体 在童年时期，绝大多数人在成年后继续与语言障碍作斗争。尽管有紧迫的 需要扩大面向成年人的语言干预， DLD患者除了童年以后的语言学习机制外， 区