Neural Mechanisms for Generating Temporal Coding

这个项目的目标是开发生物物理模型和相应的数学技术，以描述通过神经元网络的活动模式产生时间代码的过程。研究人员专注于一种名为相位进动的强健时间代码，这是在实验中发现的，在快速运动的大鼠海马区锥体细胞的放电模式中。这个时间代码被认为是动物在已知环境中的位置信号。研究人员采用了由三种互补的方法组成的建模方法：简化神经元网络的数学分析，生物物理神经元网络的模拟，以及结合和解释自由运动大鼠的实验记录的功能建模。数学方法使用几何奇异微扰理论，利用细胞的内在描述和这些细胞之间的突触所固有的多重时间尺度。模拟是基于电导的神经元的穿透网络。研究人员之前开发的遗传算法和分叉延续程序有助于分析模拟结果。分析和模拟的一个目标是做出实验上可验证的预测。海马体是癫痫和阿尔茨海默病的主要靶点，在记忆功能和空间导航能力方面具有公认的作用。海马神经元之间的动态相互作用可以用时间编码方案来描述。为了检测这些神经元的潜在病理动力学，有必要首先了解这些编码方案是如何在正常情况下构建的。更广泛地说，神经科学的一个基本目标是从单个神经元水平到系统水平了解功能。这个项目的目标是连接一个特定系统--海马体--的所有细节水平。这项工作也将为大脑中存在时间代码的其他区域的研究奠定数学基础。该项目的资金由计算数学计划和MPS多学科活动办公室以及生物计算神经科学计划提供。

Bose9973230 The goal of this project is to develop biophysical modelsand the accompanying mathematical techniques to describe thegeneration of temporal codes by the activity patterns of networksof neurons. The investigators focus on a robust temporal code,called phase precession, that has been experimentally found inthe firing pattern of pyramidal cells in the hippocampus offreely moving rats. This temporal code is believed to signal theanimal's location in a known environment. The investigators applya modeling approach consisting of three complementary methods:mathematical analysis of networks of simplified neurons,simulations of networks of biophysical neurons, and functionalmodeling that incorporates and interprets experimental recordingsfrom freely moving rats. The mathematical approach, usinggeometric singular perturbation theory, exploits the multipletime scales inherent in the intrinsic descriptions of the cellsand the synapses between these cells. Simulations are performedon networks of conductance based neurons. Genetic algorithms,previously developed by the researchers, and bifurcationcontinuation programs aid in analyzing the simulation results. Agoal of the analysis and simulations is to make experimentallyverifiable predictions. The hippocampus is a primary target for epilepsy andAlzheimer's Disease and has a well established role in memoryfunction and in spatial navigation abilities. The dynamicalinteraction between neurons in the hippocampus may be describedusing temporal coding schemes. In order to detect potentiallypathological dynamics of these neurons, it is essential to firstunderstand how these coding schemes are constructed under normalcircumstances. More generally, a fundamental goal of neuroscienceis to understand function from the single neuron level to thesystems level. The objective of this project is to bridge all ofthe levels of detail for one specific system, the hippocampus.This work will also lay the mathematical foundation for researchin other areas of the brain where temporal codes exist. Fundingfor the project is provided by the program of ComputationalMathematics and the Office of Multidisciplinary Activities in MPSand by the Computational Neuroscience program in BIO.