MECHANISMS AND MODELING OF NETWORKED CIRCADIAN PACEMAKER SYNCHRONIZATION
MECHANISMS AND MODELING OF NETWORKED CIRCADIAN PACEMAKER SYNCHRONIZATION
批准号:
8515466
负责人:
FRANCIS J DOYLE
金额:
$26.73万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-01 至 2015-07-31
关键词:
AdultBehaviorBilateralBiologicalBiological Neural NetworksBrainCell CommunicationCellsCircadian RhythmsClinicalCognitiveComputer SimulationComputing MethodologiesCoupledCouplingCuesDataDevelopmentEquationFetal DevelopmentGene ExpressionGraphHeterogeneityHormonesIndividualKineticsLengthMapsMeasurementMeasuresMediatingMetabolismMethodsMetricModelingMonitorMood DisordersNeuronsNoiseOutputPathway AnalysisPerformancePhasePhysiologyPreventionProcessPublic DomainsRegulationRelative (related person)ResolutionRoleSeriesSignal TransductionSleep DisordersSleep Wake CycleSolutionsSourceStatistical ModelsSystemTimebasecircadian pacemakerfetalhigh end computermodels and simulationnetwork modelsnovelprogramsresearch studyrestorationspatiotemporalstatisticssuprachiasmatic nucleustheoriestool
中文摘要
描述(由申请人提供):哺乳动物视交叉上核(SCN),行为和生理的日常循环所必需的。SCN细胞如何同步协调行为在很大程度上是未知的。我们已经建立了一个结合实验和计算方法的合作项目来研究大量的昼夜节律振荡器,它们的联系,以及它们自我同步和响应环境时间线索扰动的实时动力学。要了解大脑内的昼夜节律调节,我们必须了解昼夜节律神经元之间的拓扑结构和相互作用的类型。Aim 1将监测SCN振荡网络在胎儿发育期间、夹带期间、相移后以及成年SCN细胞间通讯恢复后的同步。使用新的基于小波的时间序列分析,我们将估计SCN中单个连接的强度和方向。目标2将使用图论和空间统计来量化发育和成年SCN的网络特征。这些分析将确定正常发育期间和环境扰动之后的同步机制,以及有助于周期精度的局部、区域或全球耦合的相对贡献。Aim 3将比较四种情况下SCN网络与确定性和随机模型网络的性能。计算模型将研究内在噪声和细胞-细胞异质性对昼夜同步的影响。揭示昼夜节律振荡器如何相互作用以产生连贯的节律输出将对预防和治疗昼夜节律中断(包括情绪和睡眠障碍)具有重要的临床意义。
英文摘要
DESCRIPTION (provided by applicant): The mammalian suprachiasmatic nucleus (SCN), required for daily cycles in behavior and physiology. How the cells of the SCN synchronize to coordinate behavior is largely unknown. We have established a collaborative program combining experimental and computational methods to study large numbers of circadian oscillators, their connections, and the real-time kinetics by which they self-synchronize and respond to perturbations in environmental timing cues. To understand circadian regulation within the brain, we must understand the topology and types of interactions between circadian neurons. Aim 1 will monitor the network of SCN oscillators as they synchronize during fetal development, during entrainment, following a phase shift, and after restoration of cell-cell communication in the adult SCN. Using novel wavelet-based time series analyses, we will estimate the strength and direction of individual connections in the SCN. Aim 2 will use graph theory and spatial statistics to quantify network features of the developing and adult SCN. These analyses will define the mechanisms of synchronization during normal development and following environmental perturbations and the relative contributions of local, regional or global coupling which contribute to period precision. Aim 3 will compare the performance of the SCN networks under the four conditions with both deterministic and stochastic model networks. The computational models will investigate the effects of intrinsic noise and cell-cell heterogeneity on circadian synchronization. Revealing how circadian oscillators interact to generate a coherent rhythmic output will have important clinical implications for prevention and treatment of circadian rhythm disruptions, including mood and sleep disorders.
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