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2016年6月22日至24日在夏威夷Lihue举行的神经活动建模会议：统计学、动态系统和网络(MONA2)。许多疾病，如ADHD、自闭症和精神分裂症，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。由于计算神经科学的目标是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对病理生理学的机械性描述。这次会议将汇集美国和日本的统计学家和计算神经学家，以加强两国科学家之间的合作。美国国家科学基金会的资助将有助于支持美国研究人员的参与。计算神经科学从神经活动的生物物理模型的成功，大脑作为计算机的隐喻的吸引力，以及统计和机器学习方法在整个科学中日益突出，朝着不同的方向发展。这帮助创造了一套丰富的与“计算”相关的想法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。尤其是，这一领域的数学研究和统计学研究几乎没有重叠之处。计算神经科学的重要突破可能来自研究策略，这些策略能够结合目前基本上不同的方法。该奖项旨在鼓励创造和加强美国和日本科学家之间的合作。欲了解更多信息，请访问会议网站http://www.stat.cmu.edu/mona2.。