AROUSAL AND ATTENTION IN HIGH RISK NEONATES

拟议的研究继续研究唤醒和 发展过程中的注意力及其对以后知觉、认知、 和自动调节系统，无论是正常婴儿还是有贫困风险的婴儿 中枢神经系统损伤导致的结果。具体目标是确定：1）早期 唤醒和注意力的神经基础； 2) 觉醒和情绪的相互作用 发展过程中的关注； 3）发展的后果 知觉、认知和注意力的觉醒和注意力的转变 自我监管的发展； 4) 验证早期评估 唤醒调节注意力（AMA）作为非典型发展的预测因子， 特别强调自我监管的结果。设计很有前瞻性， 两个队列的两层纵向研究：来自 336 名新招募的婴儿 NICU 对 285 名儿童进行了从出生到 34 个月的跟踪研究 婴儿时期，并在该项目中对 34 至 60 个月大的婴儿进行跟踪调查。 将在后续年龄（4、 新队列为 10、16、25 和 34 个月，新队列为 34、42、51 和 60 个月 现有队列）。重点是神经生理学测量（视觉和 听觉诱发电位）在新生儿时期，行为测量 第一年及更高阶的自动监管和 AMA 流程 后期执行控制措施，以便了解 每个时期这些过程的前因和后果。结果将是 使用包括 GEE 在内的多变量、多层次统计程序进行分析 和 SEM（视情况而定）。

The proposed research continues a study the process of arousal and attention during development and its influence on later perceptual, cognitive, and autoregulatory systems, in both normal infants and infants at risk for poor outcome due to CNS injury. The specific aims are to determine: 1) the early neural substrates of arousal and attention; 2) the interaction of arousal and attention across development; and 3) the consequences of developmental transitions in arousal and attention for perceptual, cognitive, and autoregulatory development; and to 4) validate an assessment of early arousal-modulated attention (AMA) as a predictor of atypical development, with particular emphasis on autoregulatory outcomes. The design is a prospective, two tiered, longitudinal study of two cohorts: 336 newly recruited infants from the NICU followed from birth to 34 months, and 285 children previously studied as infants, and followed in this project from 34 to 60 months of age. Hypotheses will be tested using a battery of assessments at follow-up ages (4, 10, 16, 25, and 34 months for the new cohort and 34, 42, 51, and 60 months for the existing cohort). Emphasis is on neurophysiologic measures (visual and auditory evoked potentials) in the newborn period, behavioral measures of autoregulatory and AMA processes during the 1st year, and higher order executive control measures at later ages, in order to understand the antecedents and consequences of these processes at each period. Results will be analyzed using multivariate, multilevel statistical procedures including GEE and SEM, as appropriate.