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

项目摘要 拟议的项目详细说明了一条创新的研究路线，它利用了网络领域的先进工具 科学阐明成人典型和非典型的语言学习机制。自然界的网络分析 语言揭示了许多从关系中涌现出来的全球结构模式(用于构建 网络边缘)单词之间(用作网络节点)。由自然产生的网络提供信息 架构真实世界的语言，我们将构建显示紧急情况的微型人工语言 现有语言系统的特性，并衡量成年人学习这些语言的程度 典型发育组(TD)和发展性语言障碍组(DLD)(目标1)。鉴于DLD 通常与加工和产生复杂形态合成的缺陷有关，我们将集中在 单词之间的边表示它们在句子中同现或在句子中重叠的网络 形态家族(例如，食者、进食)。在目标2中，我们将研究成年人是否存在语言学习障碍 使用DLD可以被重塑为对局部级别信息的超聚焦(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 在语言学习障碍和表达语言之间，目标3呼吁对引出的语言进行网络分析 语音样本揭示个体在学习过程中是否对复杂性不那么敏感 他们的语言输出很复杂。被诊断为接受性和表现性语言障碍的个人 在童年，绝大多数人在成年后仍在与语言障碍作斗争。尽管迫不及待 需要扩大面向成人的语言干预措施，全面描述#年缺陷的特征 患有DLD的人，除了他们童年以后的语言学习机制外，还没有得到充分的研究 区域。

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.