Statistical Analysis of Neural Data (SAND9)

第九届神经数据统计分析国际研讨会(SAND9)将于2019年5月21日至23日在宾夕法尼亚州匹兹堡举行。其目的是确定神经数据分析中的重要挑战和攻击它们的有用策略。SAND9将汇集对神经数据定量分析感兴趣的神经生理学家、统计学家、数学家、工程师、物理学家和计算机科学家。会议将包括8场主旨讲座，5名受邀的讨论者，12名初级调查人员根据摘要竞争挑选的讲座，一次海报会议，以及关于脑科学几个领域新出现的挑战的小组讨论。SAND9是2002年开始的一系列讲习班中的第九期。研讨会于春季在认知神经基础中心举行，该中心由卡内基梅隆大学和匹兹堡大学联合运营。与以往的SAND会议一样，SAND9旨在促进实验神经科学家和那些接受过统计和计算方法培训的人之间的交流；鼓励年轻研究人员介绍他们的工作并从更资深的研究人员那里获得反馈；并将妇女、代表性不足的少数群体和残疾人作为参与者，他们可能会从小研讨会环境中受益。发现行为神经基础的实验方法一直在快速发展，其结果是，大脑数据集的大小和复杂性都在增加。迫切需要更好地理解如此丰富的数据集的方法，这些数据集可以使设计出更多信息量更大的实验。这一系列研讨会涉及识别、讨论和传播许多最有前途的各种神经数据分析方法，包括从显微镜、电生理学、钙成像、电路刺激和神经成像获得的数据。更多细节请参见http://sand.stat.cmu.edu/This奖项，该奖项反映了国家科学基金会的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The ninth international workshop on Statistical Analysis of Neural Data (SAND9) will take place May 21-23, 2019, in Pittsburgh, PA. Its purpose is to define important challenges in the analysis of neural data and useful strategies for attacking them. SAND9 will bring together neurophysiologists, statisticians, mathematicians, engineers, physicists, and computer scientists who are interested in quantitative analysis of neural data. The meeting will include 8 keynote lectures, with 5 invited discussants, 12 lectures by junior investigators chosen competitively based on abstract submissions, a poster session, and a panel discussion of emerging challenges across several areas of brain science. SAND9 is the ninth workshop in a series that began in 2002. The workshops are held during the spring at the Center for the Neural Basis of Cognition, run jointly by Carnegie Mellon University and the University of Pittsburgh. Like past SAND meetings, SAND9 aims to foster communication between experimental neuroscientists and those trained in statistical and computational methods; to encourage young researchers to present their work and get feedback from more senior investigators; and to include as participants women, under-represented minorities, and persons with disabilities, who might benefit from the small workshop environment. Experimental methods for discovering the neural basis of behavior have been advancing rapidly and, as a result, brain data sets are increasing in size and complexity. Methods for better understanding such rich data sets, which can enable design of ever-more informative experiments, are desperately needed. This workshop series is concerned with identifying, discussing, and disseminating many of the most promising approaches to analysis of neural data of all kinds, including data obtained from microscopy, electrophysiology, calcium imaging, circuit stimulation, and neuroimaging. More details are available at http://sand.stat.cmu.edu/This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.