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4月12日波士顿大学张希昀学术报告预告
作者:cwj 发布日期:2019-04-08 浏览次数:

报告题目:Network physiology: Fundamental Laws of Physiological Network Regulation and New Paradigm of Health and Disease

 讲 人:张希昀(波士顿大学)

报告时间:412日(周五)上午 09:30

报告地点:屏峰校区计算机大楼A411

报告摘要:

Identifying and quantifying dynamical networks of diverse systems with different types of interactions is essential to understand the mechanisms underlying the physiological regulation of organ networks. Utilizing a novel approach based on the concept of Time Delay Stability (TDS), we demonstrate how diverse physiological systems in the human organism dynamically interact as a network to generate distinct physiological states and functions, how physiological network topology and function evolve with aging, and how these organ networks breakdown with disease. Applying a system-wide integrative approach, we identify distinct patterns in the network of organ interactions across physiological states and age groups, establish first maps representing physiologic network interactions, track the evolution of organ networks with aging, and derive basic rules underlying the complex hierarchical reorganization in subnetworks of physiologic interactions (brain-brain, brain-organ and organorgan) with transitions across physiologic states. Our findings demonstrate a robust association between network characteristics and physiologic function, reveal previously unknown laws of physiological regulation, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among diverse organ systems, how physiological networks gradually change with aging while preserving key modalities, and how pathological conditions impact the network configuration.

报告人简介:

张希昀博士毕业于华东师范大学物理系理论物理专业,现在在美国波士顿大学物理系做博士后。他的研究兴趣包括非线性动力学,复杂网络与复杂系统,时间序列分析,生理学病理学数据分析等。他的具体研究内容涉及复杂网络上非线性耦合振子的同步化现象,特别是爆炸式同步现象及其产生机制;小鼠睡眠信号的精细时空结构及睡眠中的自组织临界现象;运用统计物理及非线性动力学概念来发展新的时间序列分析方法;构建人体器官耦合网络并追踪器官耦合网络随年龄变化,以及不同生理学病理学状态对器官耦合网络的影响。张希昀博士已经在主流及顶级杂志上发表了十多篇论文,其中的《Explosive synchronization in adaptive and multilayer networks》发表在物理类顶级期刊Physical Review Letters上并被编辑部选为当期的编辑推荐论文。