Conference Proposal: Statistical Modeling and Data Analysis for Neural Coding

会议提案：神经编码的统计建模和数据分析

• 批准号: 0934052
• 负责人: Lucien J. Bienenstock
• 金额: $ 0.5万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0934052&HistoricalAwards=false
• 关键词: Conference; Proposal; Statistical; Modeling; Data

Understanding the nature of the neural code is of intrinsic scientific interest since it brings us closer to understanding the computational basis of intelligence. In addition, technical advances have made it possible to monitor the activity of populations of neurons in human subjects. The volume of data generated by multiple-neuron recordings poses significant challenges for data analysis. The development of new statistical techniques is necessary to provide a meaningful basis for testing hypotheses about the nature of neural coding. One concrete example is in the area of neuronal synchrony. The coordination on a short time scale of neuronal populations has been suggested as the basis for multiple neural processes such as attention and feature binding. However, the co-variation in firing rates among neurons, especially on a short time scale, poses significant practical challenges to specifying appropriate data analysis and statistical methods.This award provides support for an international symposium on the topic of Statistical Modeling and Data Analysis for Neural Coding to be held in conjunction with the International Statistics Institute's biennial meeting at Durban, South Africa, August 2009. This symposium will bring together several statistical experts on neural coding to discuss a range of approaches to this problem. These approaches include both the generation of surrogate data sets and new statistical methods. These statistical methods may also have value for other scientific areas where multiple elements show short time scale temporal co-variation. The symposium is part of a large meeting of statistical experts. In addition to bringing together the symposium speakers to address this issue, the symposium will expose the larger statistical community to these questions and to the new statistical approaches. As the meeting will be happening on the African continent, the meeting provides an opportunity for education and outreach to African university and graduate students.

理解神经编码的本质具有内在的科学意义，因为它使我们更接近理解智能的计算基础。此外，技术进步使得监测人类受试者中神经元群体的活动成为可能。多神经元记录产生的大量数据对数据分析提出了重大挑战。新的统计技术的发展是必要的，以提供一个有意义的基础来检验关于神经编码的性质的假设。一个具体的例子是在神经元同步领域。神经元群体在短时间尺度上的协调被认为是多个神经过程（如注意力和特征结合）的基础。然而，神经元之间的放电率的共同变化，特别是在短时间尺度上，对指定适当的数据分析和统计方法提出了重大的实际挑战。该奖项为将于2009年8月在南非德班举行的国际统计研究所两年一度的会议上举行的关于神经编码的统计建模和数据分析主题的国际研讨会提供了支持。本次研讨会将汇集几位神经编码的统计专家，讨论解决这个问题的一系列方法。这些方法包括生成替代数据集和新的统计方法。这些统计方法也可能有价值的其他科学领域，多个元素显示短时间尺度的时间协变。这次专题讨论会是统计专家大型会议的一部分。除了将专题讨论会的发言者聚集在一起讨论这一问题外，专题讨论会还将使广大的统计界了解这些问题和新的统计方法。由于会议将在非洲大陆举行，会议为非洲大学和研究生提供了一个教育和外联机会。