讲座题目： Activation discovery with FDR control Application to fMRI data

主讲人：王兆军教授 南开大学

讲座时间：2022年5月11日下午14点-15点

讲座地点：腾讯会议号：518 222 217

主讲人简介：

王兆军，南开大学统计与数据科学学院教授、博士生导师、执行院长和党总支书记，统计研究院院长，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，中国现场统计研究会副理事长，中国工业统计教学研究会副会长，天津数据科学与技术学会理事长，天津市学位委员会数学与统计学科评议组召集人，曾获国务院政府特殊津贴，全国百篇优博指导教师，教育部全国高校自然科学奖二等奖及天津市自然科学奖一等奖。王兆军教授的主要研究方向包括统计过程控制(SPC)、非(半)参数回归、降维、高维数据分析、变点等，已在Journal of the American Statistical Association、Annals of Statistics、Biometrika、Statistica Sinica等专业顶级期刊上发表高质量学术论文110余篇，先后主持国家自然科学基金重点项目、面上项目、教育部博士点基金项目等10余项，现担任Statistical Theory and Related Fields、《统计信息论坛》、《数学进展》等杂志编委和《数理统计与管理》等杂志副主编。

主讲内容：

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.