Mathematical Sciences: Statistical Inference for Some Dynamic and Spatial Phenomena

数学科学：一些动态和空间现象的统计推断

• 批准号: 9208683
• 负责人: David Brillinger
• 金额: $ 5.5万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-08-01 至 1994-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9208683&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Statistical; Inference; Some

This project addresses the mathematical representation of arrays of biological neurons that are firing simultaneously with the goal of inferring their causal connections or influence diagram on the basis of firing times. The methodology of point processes of several types will be extended to include full likelihood and second-order procedures to extend the results from social scientists' path analysis and causal modeling. For small net works of two or three neurons, partial coherence analysis and threshold modeling have proved effective; however, for data for a larger network with eight neurons, nontrivial extensions are needed for display and for analysis. Physiologically, neurons communicate with each other via spike trains, emitting pulses that go on to influence other neurons; and the neurons are themselves influenced. The goal of this research is to infer the connection lines or "wiring diagram" of a network of neurons by observing their individual firing times.

这个项目解决的数学表示 生物神经元的阵列， 推断其因果关系或影响的目标 图中是根据点火时间绘制的。 点的方法论 几种类型的进程将扩展到包括完整的 可能性和二阶程序来扩展结果， 社会科学家的路径分析和因果建模。 小 网络的两个或三个神经元，部分相干分析， 阈值建模已被证明是有效的;然而，对于 具有八个神经元的更大的网络，非平凡扩展是 用于显示和分析。 从生理学上讲，神经元通过 尖峰序列，发射脉冲，继续影响其他人， 神经元;神经元本身也受到影响。 的目标 这项研究是为了推断连接线或“布线 通过观察神经元的个体， 射击时间