Predicting Autism through Behavioral and Biomarkers of Attention in Infants

了解自闭症的早期预测因素对于促进早期识别、诊断和治疗至关重要。虽然异常的视觉注意力是自闭症最早被发现的预测因素之一，并可能在自闭症固有的社会交流缺陷中发挥不可或缺的作用，但对婴儿时期出现非典型注意力的了解很少。目前的建议试图通过将认知和发展神经科学方法整合到多组前瞻性纵向设计中来表征自闭症患者异常注意的发展。方法将包括计算机化的注意定向和视觉偏好范例，与同时测量的心脏定义的持续注意相结合。将行为和心脏定义的测量结合起来，将关键地告知行为眼动是否反映了潜在的刺激反应的认知过程。行为和生物标记物的模式将在自闭症儿童(ASIBS)的高危婴儿兄弟姐妹(ASIBS)、患有脆性X综合征(FXS)的高危婴儿(FXS)和低风险对照组中进行比较；从而告知早期注意指标的病因特异性，这对早期诊断和治疗工作至关重要。具体地说，我们的目标是：(1)评估6个月、9个月和12个月(FXS中为9个月和12个月)的注意定向(脱离、促进)和视觉偏好(社交/非社交、新奇/熟悉)的群体差异；(2)比较计算机化注意范式下的行为表现与心脏定义的持续注意；以及(3)评估24个月自闭症患者的结果与这些早期行为和注意生物标志物之间的关系。多水平模型将被用来分析高危人群的注意力模式，以及早期注意力和自闭症结果之间的关系。这项研究的创新之处在于，它首次将同时测量的行为和心脏定义的注意力应用于对自闭症婴儿注意力的前瞻性监测，并比较了高危ASIBS和患有FXS的婴儿的注意行为和生物标志物。

Understanding the early predictors of autism is essential to promoting earlier identification, diagnosis and treatment. Although aberrant visual attention is one of the earliest identified predictors of autism and may play an integral role in the socio-communicative deficits inherent in the disorder, the emergence of atypical attention in infancy is poorly understood. The present proposal seeks to characterize the development of aberrant attention in autism by integrating cognitive and developmental neuroscience methods within a multiple-group, prospective longitudinal design. Methods will include computerized attention orienting and visual preference paradigms integrated with concurrently-measured heart-defined sustained attention. Integrating behavioral and heart-defined measures will critically inform whether behavioral eye movement reflects underlying cognitive processes of stimulus response. Patterns of behavioral and biomarkers will be compared across high risk infant siblings of children with autism (ASIBS), high risk infants with fragile X syndrome (FXS), and low risk controls; thus informing the etiological specificity of early attention indicators, which is essential to informing early diagnostic and treatment efforts. Specifically, we aim to: (1) evaluate group differences in attention orienting (disengagement, facilitation) and visual preference (social/nonsocial, novel/familiar) between 6, 9, and 12 months of age (9 and 12 months in FXS), (2) compare behavioral performance on computerized attention paradigms to heart-defined sustained attention, and (3) evaluate the relationship between autistic outcomes at 24 months and these early behavioral and biomarkers of attention. Multilevel modeling will be used to analyze the patterns of attention across high risk groups, as well as the relationship between early attention and autistic outcomes. This study is innovative in that it is the first to apply concurrently-measured behavioral and heart-defined attention to the prospective surveillance of infant attention in autism, as well as to compare behavioral and biomarkers of attention across high risk ASIBS and infants with FXS.