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Neural assays and longitudinal assessment of infants at very high risk for ASD

Neural assays and longitudinal assessment of infants at very high risk for ASD
自闭症谱系障碍极高风险婴儿的神经分析和纵向评估
批准号:
8906523
负责人:
SCOTT P JOHNSON
金额:
$18.57万
依托单位国家:
美国
项目类别:
财政年份:
--
资助国家:
美国
项目状态:
已结题
起止时间:
至 2016-05-31

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英文摘要
It is essential to identify the early signs of autism spectrum disorders (ASD) in order to improve developmental outcomes. While recent evidence suggests that the assessment of a wide range of skills and behaviors may help identify signs of ASD in the second year of life, the search for behavioral markers of ASD in the first 12 months has proven particularly challenging. This challenge is likely due to the limited behavioral repertoire of infants in the first year of life, thus motivating the search for more sensitive biomarkers. Informed by our own (and others') work on the neural basis and early indicators of ASD, the overarching aim of Project I is to identify reliable biological markers of ASD in infants at ultra-high risk (UHR) for the disorder, i.e. having more than one older sibling with ASD. We are taking an innovative, hypothesis driven, multi-modal approach, which uses eye tracking, pupillometry, electrophysiology (EEG), and magnetic resonance imaging (MRI) to track these infants' development in the first year of life, with focus on social attention, implicit learning, and brain connectivity. Accordingly, we will quantify the development of attention to, and engagement with, socially relevant stimuli, using eye-tracking and pupillometry paradigms capturing dynamic social interactions. We will examine the neural correlates of implicit learning using innovative event-related electrophysiological measures and functional MRI. And we will characterize the development of functional and structural connectivity using EEG and MRI. Overall, we expect to detect altered developmental pathways in these social and cognitive domains and neural processes in UHR infants, as compared to low risk infants (LR), and that the proposed measures will be predictive of an ASD diagnosis at 36 months.
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