NONLINEAR MODEL OF HIPPOCAMPUS

海马体非线性模型

• 批准号: 6120734
• 负责人: THEODORE W BERGER
• 金额: $ 13.56万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-09-30 至 1999-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6120734
• 关键词: bioengineering /biomedical engineering; biomedical resource; model design /development; nervous system; psychology; technology /technique

During this past year we have made major progress on developing and applying several of the essential modeling methodologies for input/output, or nonparametric, models of point-process input neural systems such as the hippocampus. First, we have pursued development and application of adaptive estimation procedures for decomposition studies of the hippocampus. Using this approach, we have been able to successfully estimate linear and nonlinear properties of negative feedback elements (analogous to inhibitory interneurons) given input/output data for only the feedthrough element in the presence and absence of inhibition, i.e., without direct observations from the feedback pathway. Second, we have developed a new means for estimating input/output properties of neural elements using artificial (feedforward) neural networks, which we have demonstrated is particularly powerful for estimating higher order nonlinearities from electrophysiological data. We are particularly excited about the potential for expanding this approach for estimating higher order cross-kernels for multiple-input conditions. Third, for the first time we have applied our nonlinear systems approach at the level of intracellularly recorded synaptic potentials. We have recently modeled the closed- and open-loop AMPA and NMDA components of glutamatergic synaptic input to hippocampal neurons, have derived a representation of the dynamics of the positive feedback to the NMDA receptor-channel, and can accurately predict control EPSPs to a wide range of input patterns. In addition, the model can account for differences between closed- and open-loop NMDA receptor-mediated synaptic responses. These are two of the most widely studied receptor subtypes, as the dynamics of their interaction determine the direction and magnitude of activity-dependent synaptic plasticity in hippocampus, neocortex, and other brain regions. Finally, we have made considerable progress in developing highly efficient circuit designs for analog VLSI implementation of kernel models of hippocampal neurons, a direction that should provide the means for developing massively parallel architectures for simulating global hippocampal system properties.

在过去的一年中，我们在发展方面取得了重大进展 并应用几种基本建模方法 输入/输出或非参数的点过程输入神经模型 海马等系统。 首先，我们追求发展 和应用自适应估计程序分解程序 海马研究。 使用这种方法，我们已经能够 成功估计负的线性和非线性特性 给定的反馈元素（类似于抑制性中间神经元） 仅在存在的情况下仅用于进料元素的输入/输出数据 没有抑制作用，即没有直接观察 反馈途径。 其次，我们为 使用人工来估计神经元素的输入/输出特性 我们已经证明的（馈电）神经网络是 特别有力，可以从 电生理数据。 我们对 扩展这种方法的潜力以估计高阶 多输入条件的跨内核。 第三，第一个 时间我们已经应用了非线性系统方法 细胞内记录的突触电位。 我们最近有 模拟了闭环AMPA和NMDA组件的建模 海马神经元的谷氨酸能突触输入已得出 代表NMDA积极反馈的动力学 受体通道，并且可以准确地将控制EPSP预测到宽 输入模式范围。 此外，该模型可以解释 闭环和开环NMDA受体介导的差异 突触反应。 这是研究最广泛的受体 亚型，因为它们相互作用的动力学决定了方向 和依赖活性突触可塑性的大小 海马，新皮层和其他大脑区域。 最后，我们有 在开发高效电路方面取得了长足进展 用于模拟VLSI实施海马内核模型的设计 神经元，应该为发展提供手段的方向 大量平行架构，用于模拟全球海马 系统属性。