Conference on Modeling Neural Activity: Statistics, Dynamical Systems, and Networks

神经活动建模会议：统计、动力系统和网络

• 批准号: 1612914
• 负责人: Robert Kass
• 金额: $ 2万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-15 至 2017-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1612914&HistoricalAwards=false
• 关键词: Conference; Modeling; Neural; Activity; Statistics

This award supports participation in the conference on Modeling Neural Activity: Statistics, Dynamical Systems, and Networks (MONA2) held June 22-24, 2016 in Lihue, Hawaii. Many disorders, such as ADHD, autism, and schizophrenia, as well as stroke and various neurodegenerative diseases, are thought to involve dysfunction of neural networks. Because computational neuroscience aims to supply principles for understanding the activity of individual and collective neural firing patterns, its successes can help in formulating mechanistic descriptions of pathophysiology. This conference will bring together statisticians and computational neuroscientists from the US and Japan in order to enhance collaborations between scientists in the two countries. NSF funding will help support the involvement of the US researchers. Computational neuroscience has grown, in distinct directions, from the success of biophysical models of neural activity, the attractiveness of the brain-as-computer metaphor, and the increasing prominence of statistical and machine learning methods throughout science. This has helped create a rich set of ideas and tools associated with "computation" to study the nervous system, but it has also led to a kind of balkanization of expertise. There is, especially, very little overlap between mathematical and statistical research in this area. Important breakthroughs in computational neuroscience could come from research strategies that are able to combine what are currently largely distinct approaches. This award seeks to encourage the creation and enhancement of collaborations between scientists from the US and Japan. More information can be found on the conference web site http://www.stat.cmu.edu/mona2.

该奖项支持参加于2016年6月22日至24日在夏威夷利休举行的神经活动建模：统计、动力系统和网络（MONA2）会议。许多疾病，如多动症、自闭症、精神分裂症，以及中风和各种神经退行性疾病，都被认为与神经网络功能障碍有关。因为计算神经科学旨在为理解个体和集体神经放电模式的活动提供原理，它的成功有助于形成病理生理学的机制描述。这次会议将汇集来自美国和日本的统计学家和计算神经科学家，以加强两国科学家之间的合作。美国国家科学基金会的资金将帮助支持美国研究人员的参与。从神经活动生物物理模型的成功、大脑即计算机比喻的吸引力，以及统计和机器学习方法在整个科学领域的日益突出，计算神经科学在不同的方向上得到了发展。这有助于创造一套丰富的与“计算”相关的思想和工具来研究神经系统，但它也导致了一种专业知识的巴尔干化。在这一领域，数学和统计研究之间的交集尤其少。计算神经科学的重要突破可能来自能够将目前基本上不同的方法结合起来的研究策略。该奖项旨在鼓励创造和加强美日科学家之间的合作。更多信息可在会议网站http://www.stat.cmu.edu/mona2上找到。