The role of short-term synaptic plasticity in feedback neuronal networks

该项目的主要目标是开发新的数学技术来研究反馈神经元网络中短时突触可塑性（STSP）的作用。 这些技术是基于从不同的前馈过程中提取反馈信息。 主要研究者将展示如何定义不同的广义响应曲线（GRC），以量化神经元如何响应前馈输入。 定义新类型的GRCs，研究STSP对这些GRCs的影响，并探索GRCs和反馈之间的联系将是该项目的主要重点。 要解决的具体问题包括确定如何在中央模式生成网络中保持相位关系，确定网络如何结合联合收割机突触和内在共振信息以选择优选的操作频率，以及了解含有T型钙电流的细胞的网络中的多稳定性的起源。 短期突触可塑性（STSP）是指突触改变其强度的能力作为其使用功能的函数。 它广泛存在于大脑的神经回路中。反馈是大多数神经元回路的共同特征。 了解它在决定节奏模式的动力学中的作用对于理解神经元网络的功能至关重要。 通过考虑STSP对反馈网络的影响，该项目将增强我们对中枢神经系统网络如何组织其组件执行咀嚼，游泳或呼吸等行为任务的理解。 由于其跨学科性质和与实验神经科学的直接联系，该项目的研究结果预计将引起更大的实验，计算和分析神经科学社区成员的兴趣。 博士后和研究生将参与该项目的各个方面，并将在数学神经科学的跨学科领域进行培训。 该项目还将直接补充2004年开始的NJIT（DUE 0436244）正在进行的NSF资助的本科生生物学和数学培训计划。 到目前为止，参加的12名本科生中有6名来自传统上在数学和科学方面代表性不足的群体。 该项目强调研究和培训，将对培养一支能够在数学和生命科学这一具有挑战性的界面上工作的训练有素的劳动力队伍产生更广泛的长期影响。

The primary goal of this project is to develop new mathematical techniques to investigate the role of short-term synaptic plasticity (STSP) in feedback neuronal networks. The techniques are based on extracting feedback information from different feed forward processes. The Principle Investigator will show how to define different generalized response curves (GRCs) that quantify how a neuron responds to feed forward inputs. Defining new types of GRCs, studying the effect of STSP on these GRCs and exploring the connection between GRCs and feedback will be a major focus of the project. Specific problems to be addressed include determining how phase relationships are maintained in central pattern generating networks, determining how networks combine synaptic and intrinsic resonance information to choose a preferred frequency of operation and understanding the origins of multi-stability in networks with cells that contain T-type calcium currents. Many of these problems are being considered in parallel with an experimental group that works on the crab stomatogastric ganglion.Short-term synaptic plasticity (STSP) refers to the ability of a synapse to change its strength as a function of its usage. It is widely found in neuronal circuits across the brain. Feedback is a feature that is common to most neuronal circuits. Understanding its role in determining the dynamics of rhythmic patterns is of critical importance for understanding the function of neuronal networks. By considering the effect of STSP on feedback networks, this project will enhance our understanding of how networks of the central nervous system organize their components to perform behavioral tasks such as chewing, swimming or breathing. Due to its interdisciplinary nature and direct link with experimental neuroscience, the findings of this project are expected to be of interest to members of the larger experimental, computational and analytic neuroscience communities. Post-doctoral and graduate students will participate in various aspects of this project and will be trained in the interdisciplinary field of mathematical neuroscience. This project will also directly complement the on-going NSF funded Undergraduate Biology and Mathematics Training Program at NJIT (DUE 0436244), which began in 2004. Six of the twelve undergraduates who have thus far participated are from groups that are traditionally under-represented in mathematics and science. With its emphasis on both research and training, this project will have a longer-term broader impact of developing a trained workforce able to work at the challenging interface of mathematics and the life sciences.