New Statistical Methods for fMRI Applied to Remapping

应用于重映射的功能磁共振成像新统计方法

• 批准号: 7185138
• 负责人: CHRISTOPHER R GENOVESE
• 金额: $ 18.02万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7185138
• 关键词: Address; Affect; Area; Binding; Brain; DNA Microarray Chip; DNA Microarray format; Data; Data Analyses; Dependence; Development; Disease regression; Experimental Designs; Eye; Eye Movements; Face; Functional Magnetic Resonance Imaging; Galaxy; Human; Image Analysis; Magnetic Resonance Imaging; Methods; Modeling; Monkeys; Morphologic artifacts; Neighborhoods; Neurons; Neurosciences; Noise; Numbers; Parietal Lobe; Perception; Personal Satisfaction; Physiology; Procedures; Process; Rate; Recurrence; Shapes; Specific qualifier value; Statistical Methods; Structure; System; Technology; Testing; Time; Visual; Work; data modeling; design; interest; model design; neuroimaging; neuromechanism; novel strategies; programs; research study; response; statistics; tool; visual information

DESCRIPTION (provided by applicant): This project consists of two intertwined components: (a) development of new statistical methods that address recurrent problems in the analysis of functional neuroimaging data and (b) neuroscientific studies of visual remapping in human cortex, which will frame the need for and guide the development of our new methods. The new statistical methods in this proposal apply directly to diverse applications beyond functional neuroimaging, from galaxy clustering to DNA microarrays. The three neurosciences questions in this proposal address fundamental issues regarding neural mechanisms of remapping in humans. Visual remapping is the process that coordinates the visual and eye-movement systems in order to maintain stable perception of the world when the eyes move. This project will achieve the following specific aims, each tied to a specific scientific question. Aim 1. To develop new multiple testing methods for false discovery control. Question 1. Does remapping occur outside parietal cortex? Extending recent work on controlling the False Discovery Rate this project will develop procedures that bound the unobserved proportion (or number) of false discoveries with specified confidence. The method will be applied to investigate Question 1. Aim 2. To develop tools for finding nonlinearly optimal fMRI designs. Question 2. What is the time course of remapping? This project will implement design tools that optimize targeted inferences -- linear and nonlinear. The tools will be applied to design experiments that address Question 2. Aim 3. To develop nonparametric confidence sets for structured function estimation. Question 3. How do the shapes of the visual and remapped responses differ? This project will build on recent work in nonparametric regression to construct confidence sets for an unknown function under shape constraints and with dependent noise. The method will be applied to Question 3.

描述（由申请人提供）：该项目由两个相互交织的组成部分组成：(a)开发新的统计方法，解决功能性神经成像数据分析中反复出现的问题；(b)人类皮层视觉重映射的神经科学研究，这将为我们的新方法的发展提供需求和指导。