ASM: Multi-Sensory Control of Tracking Behavior in Weakly Electric Fish

ASM：弱电鱼跟踪行为的多感官控制

• 批准号: 0543985
• 负责人: Noah Cowan
• 金额: --
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2009-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0543985&HistoricalAwards=false
• 关键词: ASM; Multi; Sensory; Control; Tracking

Project AbstractASM: Multi-Sensory Control of Tracking Behavior in Weakly Electric FishPI: Noah J. Cowan, Dept. of Mechanical Engineering, Johns Hopkins UniversityCo-PI: Eric S. Fortune, Dept. of Psychological and Brain Sciences, Johns Hopkins UniversityIntellectual Merit- A tightly integrated and multidisciplinary approach using a uniquely suited model system will help answer a fundamental question in sensorimotor integration: how is information processed by the nervous system to control locomotion?In the model system, weakly electric fish robustly and naturally swim back and forth to stabilize visual and/or electrosensory images, just as humans smoothly track moving objects with their eyes to stabilize visual images. This collaborative work builds on the strengths of the PI, a modeler of sensorimotor locomotion systems and the Co-PI, an organismal sensory neurobiologist.The approach incorporates mathematical modeling, behavioral experiments, and neurophysiological analyses. A mathematical model of the tracking behavior makes specific, testable predictions of both behavior and neural processing. The model's predictions of behavior will be tested by systematically varying visual and electrosensory information available to the fish for tracking a moving sensory image. The model's predictions will also be tested using central nervous system recordings in awake, behaving animals. The stimuli will include signals identical to those used for behavioral experiments, whose input-output relations are predictable from the model. Broader Impacts Undergraduate and graduate trainees will receive multidisciplinary training in neuroscience, experimental design, data collection and analysis, and computational modeling. Further, we will co-teach a new undergraduate course in sensor-based animal locomotion, and a companion graduate seminar. Finally, the study of sensorimotor animal behaviors has greatpotential to inspire novel strategies for autonomous control in artificial systems.

项目摘要ASM：弱电鱼跟踪行为的多感官控制PI：诺亚J.科万，系。约翰霍普金斯大学机械工程系副教授。Fortune，Dept.约翰霍普金斯大学心理学和脑科学系的博士学位。智力优势--一种紧密结合的多学科方法，使用一种独特的模型系统，将有助于回答感觉运动整合中的一个基本问题：神经系统如何处理信息来控制运动？在模型系统中，弱电鱼健壮而自然地来回游动以稳定视觉和/或电感觉图像，就像人类用眼睛平滑地跟踪移动的物体以稳定视觉图像一样。这项合作工作建立在PI（感觉运动系统的建模者）和Co-PI（生物体感觉神经生物学家）的优势之上。该方法结合了数学建模、行为实验和神经生理学分析。跟踪行为的数学模型对行为和神经处理做出了具体的、可测试的预测。该模型的行为预测将通过系统地改变视觉和电感觉信息提供给鱼跟踪移动的感觉图像进行测试。该模型的预测也将使用清醒的行为动物的中枢神经系统记录进行测试。刺激将包括与用于行为实验的信号相同的信号，其输入-输出关系可以从模型中预测。本科生和研究生学员将接受神经科学、实验设计、数据收集和分析以及计算建模等多学科培训。此外，我们将共同教授一门新的基于传感器的动物运动本科课程，以及一个同伴研究生研讨会。最后，对感觉运动动物行为的研究有很大的潜力，可以激发人工系统自主控制的新策略。