Longitudinal measurements of sleep EEG in adolescence

描述：（由申请人提供）青春期现在被认为是一个时期 主要的大脑重组，除了快速的内分泌和身体 发展最突出的大脑变化之一是总的减少 睡眠和一个巨大的下降幅度和丰富的δ脑电图的 NREM睡眠。青春期的其他大脑变化包括突触消除， 皮质代谢率降低神经发育模型表明， 精神分裂症可能是由这些成熟的异常引起或暴露的。 流程.白天嗜睡出现在青春期，影响情绪和学校 性能然而，一项关于白天和夜间的关系的特定的受试者内研究 睡眠脑电图波形的定量变化， 报道 在我们的知识中还有其他重大的空白。我们不知道主体内部 δ和其他EEG波的振幅和发生率的变化率 频率，三角洲下降中的“爆发”是否正常发生， 年龄曲线，它们与年龄和青春期的关系，以及 个人和性别差异。我们的研究旨在填补这些空白， 在2个年龄组（9-13岁和12-16岁）中纵向研究睡眠 在变化最快的时期。基线和延长睡眠将是 每年学习两次，为期4年。EEG波形将通过以下方式进行量化： FFT-频谱和周期振幅分析（两种最广泛使用的计算机 方法）和视觉睡眠阶段评分。嗜睡将通过以下方式进行评估： 将系统地评估情绪、行为评级和情绪， 每个时间点。 拟议中的研究将有助于填补我们对其中一种 人类大脑最明显的成熟变化，它也将测试 关于这些变化的相关性的具体假设。数据我们 获取可以揭示伴随的大脑变化，导致 识别新的生物学关系。我们的研究还将提供 精神病患者神经发育研究的基准数据 青少年和“高危”人群。

DESCRIPTION: (provided by applicant) Adolescence is now recognized as a period of major brain-reorganization, in addition to rapid endocrine and physical development. Among the most prominent brain changes are reductions in total sleep and a huge decline in the amplitude and abundance of the delta EEG of NREM sleep. Other brain changes in adolescence include synaptic elimination and a reduction in cortical metabolic rate. Neurodevelopmental models posit that schizophrenia may be caused or unmasked by abnormalities in these maturational processes. Daytime sleepiness emerges in adolescence, impacting mood and school performance. However, a specific within-subjectstudy of the relation of daytime sleepiness to quantitative changes in sleep EEG waveforms has not been reported. There are other major gaps in our knowledge. We do not know the within-subject rates of change in the amplitude and incidence of EEG waves in delta and other frequencies, whether 'spurts' in delta decline normally occur, the shapes of the age curves, their relation to age vs. pubertal stage, and the extent of individual and gender differences. Our research aims to fill these gaps by studying sleep longitudinally in 2 age cohorts (ages 9-13 and 12-16 years) during the period of most rapid change. Baseline and extended sleep will be studied twice/yr for 4 years. EEG waveforms will be quantified with FFT-spectral and period amplitude analyses (the 2 most widely used computer methods) and with visual sleep stage scoring. Sleepiness will be assessed with the MSLT and behavioral ratings and mood will be systematically evaluated at each time point. The proposed research will help fill major gaps in our knowledge of one of the most pronounced maturational changes of the human brain, It will also test specific hypotheses regarding the : correlates of these changes. The data we acquire could shed light on concomitant brain changes, leading to the identification of new biological relationships. Our studies will also provide benchmark data for neurodevelopmental studies in psychiatrically ill adolescents and 'at-risk' population.