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Activation discovery with FDR control: Application to fMRI data

2021-12-16
Speaker: WANG Zhaojun, Professor, School of Mathematical SciencesNankai University

Venue: Tencent meeting ID: 615-465-700

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.