Conference: ICN, University of Maryland 2012, August 5-10, 2012

会议：ICN，马里兰大学 2012，2012 年 8 月 5-10 日

• 批准号: 1226873
• 负责人: Cynthia Moss
• 金额: $ 1.5万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-15 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1226873&HistoricalAwards=false
• 关键词: Conference; ICN; University; Maryland; 2012

This proposal requests funds to cover registration costs for graduate students and postdoctoral attendees, as well as for local reporters and undergraduates to attend the 10th International Congress of Neuroethology (ICN), to be held on August 5-10, 2012, at the University of Maryland in College Park. Topics to be covered at the meeting include sensory processing and perception, multisensory signaling, locomotion and motor control, behavioral endocrinology, and genetic control of behavior. Some sessions will highlight new technologies, such as automated analysis of complex behaviors emerging in animal groups and optogenetics. The program is designed to incorporate discussion of brain function at different levels of analysis (from biophysics to field behavior) using a wide range of tools and techniques (including those drawn from physics, mathematics, signal processing, molecular biology, genomics, field observations, psychophysics, and neurophysiology) and examined in a diversity of species, both vertebrate and invertebrate. These different approaches are bound together by a common fundamental goal: to uncover neural, computational, and design solutions to natural biological problems that, once identified, can more easily pursued in other species or implemented technologically.

该提案要求提供资金，以支付研究生和博士后与会者的注册费用，以及当地记者和本科生参加将于2012年8月5日至10日在马里兰州大学帕克分校举行的第10届神经行为学国际大会（ICN）的费用。会议涉及的主题包括感觉处理和感知，多感觉信号，运动和运动控制，行为内分泌学和行为的遗传控制。一些会议将重点介绍新技术，如动物群体和光遗传学中出现的复杂行为的自动分析。该计划旨在将大脑功能的讨论纳入不同层次的分析（从生物物理学到现场行为），使用广泛的工具和技术（包括从物理学，数学，信号处理，分子生物学，基因组学，现场观察，心理物理学和神经生理学中提取的工具和技术），并在脊椎动物和无脊椎动物的物种多样性中进行检查。这些不同的方法被一个共同的基本目标联系在一起：揭示自然生物问题的神经，计算和设计解决方案，一旦确定，可以更容易地在其他物种中实现或技术实现。