Signal Models for Neuronal and Electrophysiological Activities - A Planning Grant Proposal

神经元和电生理活动的信号模型 - 规划拨款提案

• 批准号: 9615565
• 负责人: Guotong Zhou
• 金额: $ 1.68万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-05-01 至 1998-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9615565&HistoricalAwards=false
• 关键词: Signal; Models; Neuronal; Electrophysiological; Activities

9615565 Zhou This project will investigate the possibility of modeling biological phenomena such as hormone release, neuron firings, and electrophysiological profiles, by viewing pertinent measurements as events with random occurrence times. Such time series and their transformations are known as point processes and filtered point processes, respectively, and their application to biological signals will offer additional insight into their mechanisms. In collaboration with a neuroscience research group at Emory University, biologically meaningful models will be explored and state-of-the-art statistical signal processing tools will be adopted to extract model parameters. Directly interpretable models and advanced signal processing methodologies are capable of explaining certain biological phenomena which may not be evident from the raw data. A formal joint proposal (with collaborators from life science fields) will be submitted at the end of the twelve-month planning period. The present planning proposal will provide support for one graduate student and release time for the PI both of which are instrumental for the success of a junior faculty entering a new interdisciplinary field. ***

9615565 Zhou该项目将研究通过将相关测量视为具有随机发生时间的事件来建模生物现象的可能性，例如激素释放，神经元放电和电生理曲线。 这样的时间序列和它们的变换分别被称为点过程和过滤点过程，它们在生物信号中的应用将为它们的机制提供更多的见解。 与埃默里大学的神经科学研究小组合作，将探索具有生物学意义的模型，并采用最先进的统计信号处理工具来提取模型参数。 直接可解释的模型和先进的信号处理方法能够解释某些生物现象，这些生物现象可能从原始数据中看不出来。 一份正式的联合提案（与生命科学领域的合作者）将在12个月的规划期结束时提交。 目前的规划建议将提供一个研究生和PI的释放时间的支持，这两者都是一个初级教师进入一个新的跨学科领域的成功工具。 ***