Temporal Patterns in Sleep Mechanisms of Learning

睡眠学习机制的时间模式

• 批准号: 6795981
• 负责人: DANIEL MARGOLIASH
• 金额: $ 25.6万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-20 至 2007-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6795981
• 关键词: behavior prediction; behavioral /social science research tag; brain electrical activity; computational neuroscience; electrophysiology; ethology; juvenile animal; learning; mathematical model; memory; method development; model design /development; neural information processing; neurophysiology; sleep; songbirds; statistics /biometry

DESCRIPTION (provided by applicant): Sleep is a universal behavior. One functional hypothesis proposes that during sleep perceptual or procedural activity experienced during the prior day is recapitulated, with some memories consolidated and others erased. This hypothesis is supported by observations of individual neurons in the zebra finch forebrain nucleus RA that exhibit neuronal replay, similar patterns of bursting activity during singing and later during undisturbed sleep and in response to song playback. Directly testing the hypothesis, however, is hampered by the lack of procedures to analyze temporal patterns of neuronal activity, especially during sleep in the absence of a time-reference. The proposed research will develop essential statistical modeling and neurophysiological experiments to directly examine functional models of sleep. In the first experiment, the hypothesis of sleep replay in RA will be rigorously statistically tested. Patten filtering methods will be developed to assess matching not only for individual bursts but also for trains of bursts. The statistical significance of replay patterns will be described and a more complete description of the replay phenomenon at the single cell level will be derived. In the second experiment, the hypothesis that sleep replay occurs in nuclei afferent to RA will be tested. The activities of different projection classes of neurons in the afferent nucleus HVc will be recorded. Information-based and metric-based alignment techniques for temporal alignment will be developed to accommodate the lower temporal resolution of these neurons, as compared to RA neurons. The internal noise, and context-dependent temporal precision will be considered to maximize spike alignment. In the third experiment, the specific hypothesis that afferent input from IMAN modifies RA activity on a nocturnal cycle will be tested. A new statistical model, adaptive pattern filtering, will be developed to assess when during sleep are burst patterns first recognized that are destined to be expressed in singing behavior the following day. The memory consolidation hypothesis will be tested by assessing the prediction that after IMAN lesions there should be fewer or no changes in RA burst patterns following periods of sleep. The fourth experiment will record directly from RA in juvenile birds learning to sing. In this case, behavior (singing) and neurophysiological activity during the day as well as during sleep is likely to exhibit high variability which will require statistical modeling. Changes in behavior will be assessed with entropy and other statistical measures. The hypothesis that RA burst patterns change during sleep in a direction that predicts singing behavior the following day will be directly tested.

描述（由申请人提供）：睡眠是一种普遍的行为。一个功能假说提出，在睡眠期间，前一天经历的知觉或程序性活动被重演，一些记忆被巩固，另一些记忆被抹去。这一假设是支持观察斑胸草雀前脑核RA表现出神经元重放，类似的模式，爆破活动在唱歌，后来在不受干扰的睡眠和响应歌曲播放的单个神经元。然而，由于缺乏分析神经元活动的时间模式的程序，特别是在没有时间参考的睡眠期间，直接测试这一假设受到阻碍。拟议的研究将开发必要的统计建模和神经生理学实验，以直接检查睡眠的功能模型。在第一个实验中，RA睡眠重放的假设将被严格的统计检验。将开发模式过滤方法，以评估匹配，不仅为个人的爆发，但也为列车的爆发。重放模式的统计意义将被描述，并在单细胞水平的重放现象的更完整的描述将被导出。在第二个实验中，睡眠重放发生在RA传入核的假设将被测试。将记录传入核HVc中不同投射类神经元的活动。基于信息和基于度量的对齐技术的时间对齐将被开发，以适应较低的时间分辨率，这些神经元相比，RA神经元。将考虑内部噪声和上下文相关的时间精度，以最大化尖峰对齐。在第三个实验中，具体的假设，从IMAN传入输入修改RA活动的夜间周期将进行测试。一个新的统计模型，自适应模式过滤，将被开发，以评估在睡眠期间的突发模式首次识别，注定要在第二天的歌唱行为表示。将通过评估IMAN损伤后RA爆发模式在睡眠期后应较少或无变化的预测来检验记忆巩固假设。第四个实验将直接从RA记录幼鸟学习唱歌。在这种情况下，白天和睡眠期间的行为（唱歌）和神经生理活动可能表现出高度的可变性，这将需要统计建模。行为的变化将通过熵和其他统计指标进行评估。将直接测试RA爆发模式在睡眠期间以预测第二天唱歌行为的方向变化的假设。