统计与数据科学系系列学术报告之四百六十期

时    间：2024年12月20日（星期五）10:30-11:30

地    点：史带楼304室

主持人：复旦大学 管理学院 统计与数据科学系 夏寅教授

报告人：Prof. Lexin Li  University of California, Berkeley

题   目：Statistical Neuroimaging Analysis: An Overview

摘   要：Understanding the inner workings of human brains, as well as their connections with neurological disorders, is one of the most intriguing scientific questions. Studies in neuroscience are greatly facilitated by a variety of neuroimaging technologies, including anatomical magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), diffusion tensor imaging, positron emission tomography (PET), among many others. The size and complexity of medical imaging data, however, pose numerous challenges, and call for constant development of new statistical methods. In this talk, I give an overview of a range of neuroimaging topics our group has been investigating, including imaging tensor analysis, brain connectivity network analysis, multimodality analysis, and imaging causal analysis. I also illustrate with a number of specific case studies, including time-varying brain connectivity analysis, kernel ordinary differential equation for brain effective connectivity analysis, and inference for multivariate mediation analysis.

个人简介：Lexin Li, Ph.D., is a Professor of Biostatistics at the Department of Biostatistics and Epidemiology, and Helen Wills Neuroscience Institute, of the University of California, Berkeley. His research interests include neuroimaging analysis, deep brain stimulation, brain-computer-interface, reinforcement learning, ordinary differential equations, tensor data analysis, and network data analysis. He is a Fellow of the American Statistical Association (ASA), a Fellow of the Institute of Mathematical Statistics (IMS), and an Elected Member of the International Statistical Institute (ISI). He is the Editor-in-Chief of the Annals of Applied Statistics for 2025-27. 

统计与数据科学系

2024-12-17