NONLINEAR DYNAMICS OF NEURONAL ENSEMBLES

神经元系综的非线性动力学

• 批准号: 6391354
• 负责人: STEVEN J SCHIFF
• 金额: $ 9.91万
• 依托单位: GEORGE MASON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-30 至 2002-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6391354
• 关键词: artificial intelligence; brain electrical activity; computational neuroscience; electric field; electroencephalography; extracellular; hippocampus; human data; intracellular; laboratory rat; microelectrodes; neural information processing; neuroanatomy; neurons; neurosurgery; noise; statistics /biometry

The PI is a Neurophysiologist and Pediatric Neurosurgeon who will be the Associate Director of Center V (Behavioral and Neurobiology Research), with special responsibility for Neurobiology programs, at the Children"s Research Institute. This RCA will permit the PI to devote nearly full time to research. Short term goals are to test the hypothesis that neuronal ensembles have nonlinear deterministic properties. If so, they will 1) have activity that can be characterized and controlled through unstable periodic orbits, 2) hen noise driven will exhibit stochastic resonance, and 3) because of coupling will exhibit generalized (nonlinear) synchrony and emergence. Long-term goals are to achieve a better understanding of neuronal network and brain behavior, and to develop novel methods of treating dynamical diseases. The research project will involve theoretical work on the detection of unstable orbits in In Vitro brain slices and human epileptic foci. Such orbit information forms a novel method of characterizing the deterministic properties of complex systems despite nonstationarity, and can be used to control those systems. Nonlinear systems also optimize their response to weak signals in the presence of noise - stochastic resonance. We will define the statistical mechanics of stochastic resonance through simultaneous measurements of single neuron and neuronal ensemble activity. Since neuronal ensembles may demonstrate nonlinear generalized synchrony, we will quantify spatio-temporal generalized synchrony through dual simultaneous single cell recordings as a function of separation in a neuronal network. Both unstable orbit detection and generalized synchrony will be used to define the emergence of nonlinear behaviors in neuronal ensembles. The results of this research will fundamentally alter the way that neuronal dynamics can be characterized and controlled, will provide a means to deal with neuronal nonstationarity, will further explain the role of noise in the nervous system, and may provide a novel approach for the control of pathological neuronal ensembles in dynamical diseases such as epilepsy, spasticity, and tremor.

PI是一名神经生理学家和儿科神经外科医生， 第五中心（行为和神经生物学研究）副主任， 特别负责神经生物学计划，在儿童的 研究院 该RCA将允许PI投入几乎全部时间 去做研究 短期目标是检验神经元集合具有 非线性确定性 如果是这样，它们将1）具有 可以通过不稳定的周期轨道来表征和控制，2） 当噪声驱动将表现出随机共振，和3）由于 耦合将表现出广义（非线性）同步和涌现。 长期目标是更好地理解神经元网络 和大脑行为，并开发新的方法来治疗动态 疾病 该研究项目将涉及检测的理论工作 体外脑切片和人类癫痫灶中的不稳定眼眶。 等 轨道信息形成了一种表征确定性的新方法 尽管具有非平稳性，但仍具有复杂系统的特性，并且可用于 控制这些系统。 非线性系统还优化了它们对 噪声存在下的弱信号-随机共振。 我们将 定义随机共振的统计力学， 同时测量单个神经元和神经元整体活性。 由于神经元集合可能表现出非线性的广义同步， 我们将量化时空广义同步通过双 同时单细胞记录作为分离的函数 神经网络 不稳定轨道探测和广义同步 将被用来定义神经元非线性行为的出现， 合奏。 这项研究的结果将从根本上改变神经元的方式 动力学可以被表征和控制，将提供一种处理 与神经元的非平稳性，将进一步解释噪声的作用， 神经系统，并可能提供一种新的方法来控制 动力性疾病如癫痫中的病理性神经元集合， 痉挛和震颤