Computational and Statistical Methods for Analysis of Neuroimaging Datasets

神经影像数据集分析的计算和统计方法

• 批准号: 9418982
• 负责人: Jonathan Cohen
• 金额: $ 13.03万
• 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: 1995
• 资助国家: 美国
• 起止时间: 1995-08-15 至 1997-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9418982&HistoricalAwards=false
• 关键词: Computational; Statistical; Methods; Analysis; Neuroimaging

9418982 Cohen It is currently possible to acquire images of the brain so as to reveal the regions that are active while people are performing particular cognitive tasks. However, massive amounts of data (many successive images ) are produced from these neuroimaging studies, and it is not clear how to efficiently analyze all of the functional information that the data contain. With this award, a research group comprised of a psychologist, statistician, computer scientist and a radiologist (headed by Dr. Jonathan Cohen) will be developing new ways to analyze large sets of neuroimages. They will improve techniques for image reconstruction, expand available statistical tools for image processing, and implement these improvements on a supercomputer. This work should greatly advance the non-invasive analysis of brain function.

小行星9418982 目前可以获取大脑的图像，以便揭示人们在执行特定认知任务时活跃的区域。 然而，从这些神经影像学研究中产生了大量的数据（许多连续的图像），并且尚不清楚如何有效地分析数据包含的所有功能信息。 有了这个奖项，一个由心理学家、统计学家、计算机科学家和放射科医生（由Jonathan Cohen博士领导）组成的研究小组将开发分析大量神经图像的新方法。 他们将改进图像重建技术，扩展可用的图像处理统计工具，并在超级计算机上实现这些改进。 这项工作将极大地推进对大脑功能的非侵入性分析。