Collaborative Research: Geometry of Group Behaviors with Application to Fish Schooling

合作研究：群体行为几何学及其在鱼群中的应用

• 批准号: 1129820
• 负责人: Maurizio Porfiri
• 金额: $ 17.66万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1129820&HistoricalAwards=false
• 关键词: Collaborative; Research; Geometry; Group; Behaviors

The research objective of this award is to test the hypothesis that collective behavior is a manifestation of an inherently low-dimensional structure underlying the group motion. This project will classify collective behaviors through the topological analysis of the corresponding manifolds and the study of measurable properties defined thereon. This research will establish computational schemes to model such low-dimensional manifolds through undirected graphs which respect underlying geodesic structures and analyze these graphs through modern methods from computational topology and information theory. The project focuses on the fish schooling phenomenon in the universal animal model of zebrafish. Experiments and simulations will be synergistically integrated to produce a comprehensive dataset for validation of the proposed data-driven dynamical systems framework while contributing to mathematical modeling of biological groups.If successful, the results of this project will provide principled and robust computational suites for the characterization of collective behavior in biological groups from raw data that can be used by a broad animal behavior community. Mathematical tools developed in this project will aid modeling of networked dynamical systems, by providing tools for model validation based on large-scale data, and image processing for data mining, by developing novel geometric classifiers for complex systems. In addition, methods developed in this project will result into new computational tools for error analysis of time-series and data-driven studies of dynamical systems with fast and slow time scales. The results will be integrated in curricula, course materials, and projects for courses in Mechanical Engineering and Mathematics to fostering outside-the-box and multidisciplinary thinking in undergraduate and graduate students. K-12 students and teachers will be introduced to dynamical systems through formal and informal learning experiences in and out of the classroom combining fish, manifolds, and complexity.

该奖项的研究目标是检验集体行为是群体运动内在低维结构的表现这一假设。本计画将借由对应流形的拓扑分析及定义于流形上的可量测性质的研究，来对集体行为进行分类。 本研究将建立计算方案，通过无向图，尊重底层测地线结构，并通过计算拓扑学和信息论的现代方法分析这些图来模拟这种低维流形。该项目的重点是斑马鱼通用动物模型中的鱼群现象。实验和模拟将协同整合，以产生一个全面的数据集，用于验证所提出的数据驱动的动力系统框架，同时有助于生物群体的数学建模。如果成功，该项目的结果将提供原则和强大的计算套件，用于从原始数据中描述生物群体的集体行为，可供广泛的动物行为社区使用。在这个项目中开发的数学工具将有助于网络动态系统的建模，通过提供基于大规模数据的模型验证工具，以及通过开发复杂系统的新几何分类器进行数据挖掘的图像处理。此外，在这个项目中开发的方法将导致新的计算工具，用于时间序列的误差分析和具有快速和慢速时间尺度的动态系统的数据驱动研究。结果将整合到机械工程和数学课程的课程、课程材料和项目中，以培养本科生和研究生的开箱即用和多学科思维。K-12学生和教师将通过正式和非正式的学习经验，在课堂内外结合鱼，流形和复杂性介绍动力系统。

项目成果

Social environment modulates anxiogenic effects of caffeine in zebrafish

• DOI: 10.1097/fbp.0000000000000415
• 发表时间: 2019-02-01
• 期刊: BEHAVIOURAL PHARMACOLOGY
• 影响因子: 1.6
• 作者: Neri, Daniele;Ruberto, Tommaso;Porfiri, Maurizio
• 通讯作者: Porfiri, Maurizio