Biography:  Zhaojun Wang (Chinese: 王兆军) is the executive dean and professor at School of Statistics and Data Science, Nankai University; “Changjiang Scholar” distinguished professor, Ministry of Education; board member of the State Council Academic Committee in Statistics; National Statistics Advisory Board Member; Vice director of China Society for Industrial and Applied Mathematics; Vice president of China Association for Industrial Statistics; Director of Tianjin Society for Industrial and Applied Mathematics; got State Council Government Allowance Laureate; National Top 100 Excellent Ph.D. Dissertations Supervisor; Tianjin Science and Technology First Prize Awardee.

Title: Activation discovery with FDR control: Application to fMRI data

Abstract: 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.