ADAPTIVE COUPLED NEURAL SYSTEM MODEL FOR HIPPOCAMPAL FUNCTION RESTORATION

海马功能恢复的自适应耦合神经系统模型

• 批准号: 8360371
• 负责人: Alan Wing Lun Chiu
• 金额: $ 10.21万
• 依托单位: LOUISIANA STATE UNIV A&M COL BATON ROUGE
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-05-01 至 2012-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8360371
• 关键词: Action Potentials; Address; Algorithms; Alzheimer' s Disease; Biological Models; Biomedical Research; Cells; Computer Simulation; Computers; Coupled; Coupling; Dementia; Electric Stimulation; Frequencies; Funding; Future; Grant; Hippocampus (Brain); Impaired cognition; In Vitro; Louisiana; Memory; Memory Loss; Modeling; National Center for Research Resources; Nervous system structure; Neurons; Principal Investigator; Reporting; Reproducibility; Research; Research Infrastructure; Resources; Signal Transduction; Slice; Source; Synapses; Training; United States National Institutes of Health; base; cost; in vitro Model; relating to nervous system; research study; restoration

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The nervous system is comprised of network of neurons connected in an intricate and organized manner. Recent research offers potential treatment options for cognitive and memory loss accompanying Alzheimer's disease and other forms of dementia using system model-based stimulation. Coupled oscillator model with tunable parameters is proposed here to address the lack of adaptivity in these models. We hypothesize that: (1) variable oscillator model parameters related to single cell synaptic memory can be expanded to represent neuronal network kernel memory for large networks; and (2) neuronal activities at selective frequencies related to memory can be enhanced depending on the orientation of electrical stimulation. During the report period, we were successful in developing and validating the oscillator models from single cell to hippocampal slice dynamics. The concept of synaptic memory for a single cell can be extended into network kernel memory, hence drastically reducing the complexity of the computer model for large neuronal assemblies. The effects of the autapses related to the firing rate of action potentials and sub-threshold oscillations were also studied. Finally, the modulation of neuronal activities using the concept of stochastic resonance was investigated in the computer model and in vitro experiments. Our experimental results indicated that 5Hz network activity can be enhanced when the field stimulation was aligned parallel to the Subiculum-CA3 junction. Enhanced 40Hz activity was observed when the stimulation was applied perpendicular to the CA3-CA1 junction. For the direction for future studies, we will investigate the effect of Poisson distributed spike train stimulation frequency on the signal variability and reproducibility of the computer and in vitro models. A new algorithm for obtaining the numerical synaptic coupling factors is currently being developed as the building block for the long term application.

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 神经系统是由以复杂和有组织的方式连接的神经元网络组成的。最近的研究使用基于系统模型的刺激为伴随阿尔茨海默病和其他形式的痴呆症的认知和记忆丧失提供了潜在的治疗选择。本文提出了参数可调的耦合振子模型，以解决这些模型自适应性不足的问题。我们假设：（1）与单细胞突触记忆相关的可变振荡器模型参数可以被扩展以表示大型网络的神经元网络内核记忆;以及（2）与记忆相关的选择性频率处的神经元活动可以根据电刺激的方向而增强。在报告期间，我们成功地开发和验证了从单细胞到海马切片动力学的振荡器模型。单细胞突触记忆的概念可以扩展到网络内核记忆，从而大大降低了大型神经元组装的计算机模型的复杂性。并研究了动作电位放电频率和阈下振荡的自诱发效应。最后，在计算机模型和体外实验中研究了利用随机共振概念对神经元活动的调制。我们的实验结果表明，当场刺激平行于下托-CA 3连接时，5 Hz网络活动可以增强。当垂直于CA 3-CA 1连接处施加刺激时，观察到增强的40 Hz活动。作为今后研究的方向，我们将探讨泊松分布的棘波串刺激频率对计算机和体外模型的信号变异性和重现性的影响。目前正在开发一种新的算法，用于获得数值突触耦合因子作为长期应用的构建块。