CRCNS: Understanding Single-Neuron Computation Using Nonlinear Model Optimization

该提案的长期目标是整合实验设计和计算 大规模参数估计促进对神经科学中心问题的理解：如何 以及树突状细胞中离子通道的亚细胞定位是否有助于单个 神经元计算这个问题只能通过使用生物物理特性被破坏的神经元来解决。 其在感官信息处理和行为产生中的作用 是很好理解的。重点将放在在突触整合中发挥关键作用的三种通道类型上： 超极化激活的，环核苷酸门控的，混合钠/钾通道，瞬时树突状细胞 钾通道和钙通道参与爆发放电的产生。具体目标将 重点（i）确定这些通道，特别是钙通道，如何促进树突状细胞 海马锥体细胞的兴奋性;以及（ii）确定相同的通道如何有助于 碰撞检测神经元中的视觉对象分割。此外，该项目将（三）制定一项 一个更广泛的、集成的大规模建模优化框架，用于研究渠道本地化的影响 关于树状计算。这一框架在所研究的两个系统中的应用将允许（iv） 将通过模型优化获得的通道分布与实验得出的通道分布进行比较，从而 揭示了它们在神经元信息处理中的作用。最后一个具体目标是：（五）传播 新开发的优化方法，以更广泛的受众，允许广泛应用的国家， 神经科学研究中的数学知识。该项目将应用先进的数学 以基于多重打靶或配置的二阶优化算法为中心的方法 与建模的神经元相关联的动态系统的离散化。该项目还将使用 电生理学和免疫染色解剖技术来确定亚细胞通道 实验定位总的来说，该项目将有助于推进对以下方面的基本知识： 亚细胞通道定位如何有助于单个神经元内的信息处理。

The long-term objective of this proposal is to integrate the design of experiments and computational large-scale parameter estimation to advance the understanding of a central problem in neuroscience: How and whether the subcellular localization of ion channels in dendritic compartments contributes to single neuron computation. This problem can only be addressed using neurons whose biophysical properties are well characterized and whose role in the processing of sensory information and the generation of behavior is well understood. The focus will be on three channel types that play a key role in synaptic integration: hyperpolarization-activated, cyclic nucleotide-gated, mixed sodium/potassium channels, transient dendritic potassium channels, and calcium channels involved in the generation of burst firing. The specific aims will focus (i) on determining how these channels, in particular calcium channels, contribute to the dendritic excitability of hippocampal pyramidal cells; and (ii) on determining how the same channels contribute to visual object segmentation in collision detecting neurons. Additionally, the project will (iii) develop a broader, integrated large-scale modeling optimization framework to study the impact of channel localization on dendritic computation. The application of this framework in the two systems studied will allow (iv) to compare channel distributions obtained by model optimization to experimentally derived ones, thus shedding light on their role in neuronal information processing. A final specific aim will be (v) to disseminate the newly developed optimization methods to a broader audience allowing the wide application of state-ofthe- art mathematical knowledge in neuroscience research. The project will apply advanced mathematical methods centered on second-order optimization algorithms based on multiple-shooting or a collocation discretization of the dynamical system associated with the modeled neurons. The project will also use electrophysiological, and immunostaining anatomical techniques to determine subcellular channel localization experimentally. Overall, the project will contribute to advance the fundamental knowledge on how subcellular channel localization contributes to the processing of information within individual neurons.