Prediction and Word Learning in Young Children with Autism Spectrum Disorder

摘要 目前的估计表明，在美国，每44名儿童中就有一人患有自闭症谱系障碍(ASD)。 许多患有自闭症的幼儿表现出语言迟缓，这通常是 他们的父母。患有自闭症的幼儿表现出明显不同于他们的神经类型的单词学习特征 (NT)同龄人，主要以非典型或延迟使用单词学习机制为特征。我们目前有 对这些差异的不完全理解。洞察语言学习的基本机制 ASD的缺陷将在缓解这些困难和支持语言学习方面取得更大的成功 人口。一种名为自闭症预测性损害(PIA)假说的理论账户显示， 解释自闭症的一些表型特征(即难以做出社会预测)。它的用处在于 然而，解释语言学习困难的理论框架在很大程度上仍然不清楚。自闭症患者 儿童在实验任务中表现出完整的统计单词学习能力。然而，考虑到孩子们学习 单词在自然的、通常是不可预测的环境中，很难追踪到不可预测的刺激 对自闭症儿童词汇学习的深刻影响。拟议项目的总体目标是 确定在ASD预测方面的既定的、领域普遍的困难可能如何影响新词学习。 该项目将使用已建立的Eyegaze方法来测试可预测和不可预测的影响 在这一人群中关于单词学习的演讲。中心假设是不可预测的上下文在 训练将不成比例地扰乱ASD儿童的单词学习，并导致不成比例的损害 涉及对象-标签配对的保留和泛化。初步数据显示，自闭症儿童 在快速映射任务中，不成比例地被不可预测的输入干扰。在PIA假说的指导下 这一强劲的初步数据，拟议的项目将解决三个具体目标。我将描述具体的目标 新词客体配对的可预测和不可预测呈现对初始词汇学习的影响 (快速映射)在自闭症幼儿中与认知匹配的NT同龄人进行比较。SPICAL AIM II将调查 自闭症幼儿初始学习的可预测性对词-宾语记忆和概括的影响 与NT对等设备相比，配对延迟很短(5分钟)。具体目标三将评估在多大程度上 儿童的特征(例如，语言和认知能力)预测了个体在单词学习中的可变性 自闭症儿童在可预测和不可预测输入后的表现。拟议的项目将是 首先，应用已建立的眼神方法论来检验这一理论框架及其在首字母词中的应用 在这一人群中学习、保持和推广。拟议中的项目的意义在于它将 自闭症的先进理论和我们对这一人群中语言学习的理解。提议的项目的 影响是，研究结果将为最佳实践和新的治疗策略提供信息，从而实现最佳语言 自闭症儿童的学习。

ABSTRACT Current estimates suggest that autism spectrum disorder (ASD) impacts 1 in 44 children in the United States. Many young children with ASD demonstrate language delays, which are often the first area of concern noted by their parents. Young children with ASD show markedly different word learning profiles than their neurotypical (NT) peers, characterized primarily by atypical or delayed use of word learning mechanisms. We currently have an incomplete understanding of these differences. Discerning the mechanisms that underlie language learning deficits in ASD will afford greater success in alleviating these difficulties and supporting language learning in this population. One theoretical account, a predictive impairment in autism (PIA) hypothesis, has shown promise for explaining some phenotypic characteristics of ASD (i.e., difficulty making social predictions). The utility of this theoretical framework for explaining difficulty with language learning, however, remains largely unclear. Autistic children show intact statistical word learning abilities on experimental tasks. However, given that children learn words in their natural, often unpredictable environments, difficulty tracking unpredictable stimuli might have profound impacts on autistic children’s word learning. The overall objective of the proposed project is to determine how established, domain-general difficulties with prediction in ASD might impact novel word learning. This project will employ established eyegaze methodology to test the impact of predictable and unpredictable presentations on word learning in this population. The central hypothesis is that unpredictable contexts during training will disproportionately disrupt word learning in children with ASD and result in disproportionate detriments to the retention and generalization of object-label pairings. Preliminary data suggest that autistic children are disproportionately disrupted by unpredictable input in a fast-mapping task. Guided by the PIA hypothesis and this strong preliminary data, the proposed project will address three specific aims. Specific Aim I will characterize the impact of predictable and unpredictable presentations of novel-word object pairings on initial word learning (fast-mapping) in autistic toddlers compared to cognitively matched NT peers. Specific Aim II will investigate the impact of predictability during initial learning on autistic toddlers’ retention and generalization of word-object pairings over a short (5-minute) delay, compared to NT peers. Specific Aim III will evaluate the extent to which child characteristics (e.g., language and cognitive abilities) predict individual variability in word learning performance following predictable and unpredictable input in autistic children. The proposed project will be the first to apply established eyegaze methodology to test this theoretical framework and its application to initial word learning, retention, and generalization in this population. The proposed project’s significance is that it will advance theories of autism and our understanding of language learning in this population. The proposed project’s impact is that findings will inform best practices and novel treatment strategies that allow for optimal language learning for autistic children.