每周论坛之六(总第170期):林盈(中山大学),2018年4月9日下午

Intrinsic Overlapping Modular Organization of Human Brain Functional Networks Revealed by A Multiobjective Evolutionary Algorithm

发布人:高级管理员 发布日期:2018-04-09
主题
Intrinsic Overlapping Modular Organization of Human Brain Functional Networks Revealed by A Multiobjective Evolutionary Algorithm
活动时间
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主讲人
林盈 (博士)

报告人介绍:

讲座介绍:

每周论坛之六 (总第170期)

报告人:林盈 (博士)

报告人单位:中山大学心理学系

题目:Intrinsic Overlapping Modular Organization of Human Brain Functional Networks Revealed by A Multiobjective Evolutionary Algorithm

时间:2018 4 9 (周一,14:20-16:00)

地点:中山大学东校园心理学系(南学院楼C座)305

报告简介

  A plethora of research on resting-state functional MRI (R-fMRI) data has revealed modularity as a fundamental characteristic of the human brain functional network. The modular structure has recently been suggested to be overlapping, meaning that a brain region may engage in multiple modules. However, not only the overlapping modular structure remains inconclusive, the topological features and functional roles of overlapping regions are also poorly understood. To address these issues, the present work utilized the maximal-clique based multiobjective evolutionary algorithm to explore the overlapping modular structure of the R-fMRI data obtained from 55 young healthy adults. Without prior knowledge, brain regions were optimally grouped into eight modules with wide overlap. Based on topological features captured by graph theory analyses, overlapping regions were classified into an integrated club and a dominant minority club through clustering. Functional flexibility analysis found that overlapping regions in both clubs were significantly more flexible than non-overlapping ones. Lesion simulations revealed that targeted attack at overlapping regions, especially those in the dominant minority club, were more damaging than random failure or even targeted attack at hub regions. Together, our findings demonstrated the highly organized overlapping modular architecture and revealed the importance as well as complexity of overlapping regions from both topological and functional aspects, which underpins its role in executing multiple tasks and maintaining information communication

报告人简介

林盈,中山大学讲师。主要研究方向为计算智能及其在复杂网络分析和教育测量中的应用。目前已在国际会议和主流期刊上发表论文20余篇,主持国家自然科学基金项目2项。