Activation discovery with FDR control: Application to fMRI data
时间：2021-12-14
阅读量：374次
- 演讲人： 王兆军教授（南开大学）
- 时间：2021年12月17日 周五上午9：00
- 地点：腾讯会议 ID：615-465-700
摘要：Data arriving in “streams” from a large number of sources is ubiquitous, a portion of which usually incurs structural changes during the time-course of data acquisition. For example, in fMRI analysis, some brain regions become active associated with task-related stimuli or even in resting-states. Such a region corresponds to an activated data stream. We are aiming to measure the uncertainty of discovering data streams in activation via the tool of the false discovery rate (FDR). Borrowing ideas from recent developments of the FDR control methodologies, we propose a simple yet effective method to achieve this purpose meanwhile taking unknown asynchronous change patterns and spatial dependence into consideration. Its validity on controlling the FDR is justified by asymptotic analysis. Numerical experiments indicate that the proposed method is both accurate and powerful. It is also applied in a real fMRI data analysis. A R package SLIP is developed to implement the proposed method.
报告人简介： 王兆军教授，南开大学统计与数据科学学院执行院长，国务院学位委员会统计学科评议组成员，国家统计专家咨询委员会委员，中国工业与应用数学学会副理事长，中国工业统计教学研究会副会长，天津工业与应用数学学会理事长。
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