Synaptic integration and firing patterns of the midbrain dopaminergic neuron

这个项目包括计算和数学研究，以阐明由中脑多巴胺(DA)神经元执行的信号处理。中枢多巴胺系统与许多行为和认知任务有关。DA神经元的高频反应是少数几个具有明确生理意义的细胞事件之一，直接的行为含义是对该细胞特性产生极大兴趣的主要决定因素。在DA细胞的两室模型中，将对对应于高频振荡开始的分叉转变进行鸭式和奇异摄动分析。为了使分析成为可能，将引入时间尺度分隔。然后，通过与仿真的比较来评估所提出的渐近逼近的精度。在形态重建中，研究人员将再现DA细胞的棘波发生机制的独特特性：1.它对亚阈值电流的依赖；2.活跃的树突特性的贡献；3.轴突的启动和棘波的两个成分的存在。建模将结合已识别电流的数据。将应用功能标准来验证模型。使用所构建的模型，将识别DA神经元的突触整合特性。将在模拟中测量在不同树枝位置诱发的单个尖峰和尖峰序列的衰减特性。由于DA神经元中轴突来源与胞体的显著空间分离，树突树有望被划分成这样一种方式，即在某些位置的突触输入仅引起体细胞或轴突尖峰。此外，神经元的区隔可能取决于刺激频率，因为远端树突和轴突的自然频率比胞体高得多。该模型将解决自发诱发的树突棘波的同步和突触输入的经典符合检测。上述研究将结合DA细胞的放电模式和棘波起始的实验数据，得出关于神经元功能特性的结论。该项目将开启新的可能性，将涉及DA细胞的各种行为功能的研究从抽象转移到生物物理背景下。它将为进一步的实验奠定基础。在分析部分，这项研究将推进对非平凡生物现象的动力学解释，并有助于将奇异摄动技术扩展到分叉边界附近。从长远来看，对DA细胞功能的了解将推动新疗法的发展，以治疗中枢多巴胺系统受损的许多疾病。这项跨学科研究将促进数学和建模方法在生物科学中的使用。这些模型将在一个公共领域数据库中提交，用于教育和科学目的。该项目将包括研究生和博士后，通过辅导和研讨会活动。该项目有可能吸引从生物学到数学科学的女学生和学者，因为女性的比例偏低。

This project involves computational and mathematical studies to elucidate signal processing performed by the midbrain dopaminergic (DA) neuron. The central dopamine system has implications in many behavioral and cognitive tasks. A high-frequency response of the DA neuron is one of a few cellular events for which a clear physiological meaning has been proposed, and an immediate behavioral implication is the main determinant for great interest in properties of this cell. In a two-compartmental model of the DA cell, the canard and singular perturbation analysis will be applied to the bifurcation transition that corresponds to the onset of high-frequency oscillations. Timescale separations will be introduced to make the analysis possible. Then, the accuracy of proposed asymptotic approximations will be evaluated by comparison with simulations. In a morphological reconstruction, the investigators will reproduce distinctive properties of the spike generation mechanism of DA cells: 1. Its dependence on the subthreshold currents; 2. the contribution of active dendritic properties; 3. axonal initiation and presence of two components of a spike. Modeling will combine data on identified currents. Functional criteria will be applied to validate the model. Using the constructed model, synaptic integration properties of the DA neuron will be identified. Attenuation properties for a single spike and spike trains evoked at different dendritic locations will be measured in simulations. The dendritic tree is expected to be compartmentalized in such a way that synaptic inputs at certain locations elicit only somatic or only axonal spiking due to a significant spatial separation of the axon origin from the soma in DA neurons. Additionally, compartmentalization of the neuron may depend on the stimulation frequency because distal dendrites and the axon have much higher natural frequencies than the soma. Synchronization of spontaneously-evoked dendritic spikes and classical coincidence detection of synaptic inputs will be addressed in the model.The above research will integrate experimental data on firing patterns and spike initiation of the DA cell to make conclusions about functional properties of the neuron. The project will open new possibilities to move the investigation of various behavioral functions involving the DA cells from the abstract to the biophysical context. It will layout the groundwork for further experiments. In its analytical part, the research will advance dynamical explanations to nontrivial biological phenomena and contribute to the extension of singular perturbation techniques to the vicinity of a bifurcation boundary. In the long perspective, understanding of DA cell functions will advance the development of new therapies to cure numerous disorders in which the central dopamine system is impaired. This interdisciplinary study will promote the usage of mathematical and modeling methods in biosciences. The models will be submitted in a public domain database to be used for educational and scientific purposes. The project will involve graduate students and postdocs, both through mentoring and by seminar activities. The project has a potential for attracting female students and scholars from biology to mathematical sciences, were women are underrepresented.