报告题目：Functional brain network identification and analysis for naturalistic neuroimaging

报告摘要

Cognitive neuroscience has traditionally focused on the design of simple tasks to isolate a particular cognitive domain for investigation. While this form of research has yielded fundamental knowledge on the functional specialization in the brain, its ecological validity remains unclear. Accordingly, a recent development in neuroimaging is to design ecologically-valid naturalistic paradigms that approximate real life scenarios, using naturalistic and dynamic stimuli such as films and music. Comparing to traditional task-based literature, studying neural processing and network interactions during natural, dynamic conditions is imperative to the understanding of human brain function, further offering a powerful tool for clinical research on brain disorders, for their high compliance and low demand. Furthermore, network representation has been the most effective model for characterizing functional characteristics of human brain, effectively reflecting the dynamic interactions of functional activities between brain regions/networks. In this talk, I will introduce our progress of naturalistic functional brain network identification methods and their applications in brain disorders.

嘉宾简介

任玉丹，西北大学信息科学与技术学院副教授、硕士生导师。分别于2013年2019年获得西北工业大学控制系学士和博士学位，师从郭雷教授。2015年至2018年曾在澳大利亚昆士兰医学研究所郭聪研究员和Michael Breakspear教授课题组交流访学。长期从事脑功能成像分析研究工作，侧重自然范式脑功能网络构建和脑疾病诊断方面的研究。主持多项国家自然科学基金和陕西省自然科学基金，同时参与多项国家重点研发计划和国家自然科学基金项目。近年来在Nature Communications, Human Brain Mapping, Cortex, MICCAI等医学影像高水平期刊和会议发表论文，其代表性研究（第一作者）通过两步式动态因果模型方法，揭示了在自然范式条件下无意识情景记忆检索过程的脑功能网络机制以及与元认知的关联，在顶级期刊Nature Communications上发表。担任Frontiers in Neuroscience和Frontiers in Computational Neuroscience期刊的Review Editor，以及NeuroImage、Frontiers in Neurology、MICCAI、ISBI等期刊及会议的审稿人。

特别感谢本次Webinar主要组织者：

周丰丰（吉林大学）